| 1. |
- Almeida, Diogo, 1991-, et al.
(författare)
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Team KTH’s Picking Solution for the Amazon Picking Challenge 2016
- 2020
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Ingår i: Advances on Robotic Item Picking: Applications in Warehousing and E-Commerce Fulfillment. - Cham : Springer Nature. ; , s. 53-62
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- In this chapter we summarize the solution developed by team KTH for the Amazon Picking Challenge 2016 in Leipzig, Germany. The competition, which simulated a warehouse automation scenario, was divided into two parts: a picking task, where the robot picks items from a shelf and places them into a tote, and a stowing task, where the robot picks items from a tote and places them in a shelf. We describe our approach to the problem starting with a high-level overview of the system, delving later into the details of our perception pipeline and strategy for manipulation and grasping. The hardware platform used in our solution consists of a Baxter robot equipped with multiple vision sensors.
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| 2. |
- Andersson, Klas, 1968-
(författare)
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Improving Fixed Wing UAV Endurance, by Cooperative Autonomous Soaring
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The ever-expanding use and development of smaller UAVs (Unmanned Aerial Vehicles) has highlighted an increasing demand for extended range and endurance for this type of vehicles. In this thesis, the development of a concept and system for autonomous soaring of cooperating unmanned aerial vehicles is presented. The purpose of the developed system is to extend endurance by harvesting energy available in the atmosphere in the form of thermal updrafts, in a similar way that some birds and manned gliders do. By using this “free” energy, considerable improvements in maximum achievable endurance can be realized under a wide variety of atmospherical and weather conditions. The work included theoretical analysis, simulations, and finally flight test- ing of the soaring controller and the system. The system was initially devel- oped as a single-vehicle concept and thereafter extended into a system consist- ing of two cooperating gliders. The purpose of the extension to cooperation, was to further improve the performance of the system by increasing the ability to locate the rising air of thermal updrafts. The theoretical analysis proved the soaring algorithm’s thermal centering controller to be stable. The trials showed the concept of autonomous soaring to function as expected from the simulations. Further it revealed that, by applying the idea, extensive performance gains can be achieved under a fairly wide variety of conditions. The cooperative soaring, likewise, functioned as anticipated and the glid- ers found, cooperated, and climbed together in updrafts. This represents the first and presumably only time cooperative autonomous soaring in this way, has been successfully demonstrated in flight. To draw further conclusions on the advantages of cooperative soaring additional flight trials would, however, be beneficial. Possible issues and limitations were highlighted during the trials and a number of potential improvements were identified. As a part of the work, trials were conducted to verify the viability to implement the system into “real world” operational scenarios. As a proof of concept this was done by tasking the autonomous gliders to perform data/communications relay missions for other UAV systems sending imagery to the ground-station from beyond line of sight (BLOS). The outcome of the trials was positive and the concept appeared to be well suited for these types of missions. The comms relay system was further developed into a hybrid system where the optimal location concerning relay performance was autonomously sought out, after-which the attentiveness then switched to autonomous thermal soaring in the vicinity of this ideal relay position. The hybrid system was tested in simulation and partially flight tested.
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| 3. |
- Bhat, Sriharsha, 1991-, et al.
(författare)
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A Cyber-Physical System for Hydrobatic AUVs : System Integration and Field Demonstration
- 2020
-
Ingår i: 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020. - : Institute of Electrical and Electronics Engineers (IEEE).
-
Konferensbidrag (refereegranskat)abstract
- Cyber-physical systems (CPSs) comprise a network of sensors and actuators that are integrated with a computing and communication core. Hydrobatic Autonomous Underwater Vehicles (AUVs) can be efficient and agile, offering new use cases in ocean production, environmental sensing and security. In this paper, a CPS concept for hydrobatic AUVs is validated in real-world field trials with the hydrobatic AUV SAM developed at the Swedish Maritime Robotics Center (SMaRC). We present system integration of hardware systems, software subsystems for mission planning using Neptus, mission execution using behavior trees, flight and trim control, navigation and dead reckoning. Together with the software systems, we show simulation environments in Simulink and Stonefish for virtual validation of the entire CPS. Extensive field validation of the different components of the CPS has been performed. Results of a field demonstration scenario involving the search and inspection of a submerged Mini Cooper using payload cameras on SAM in the Baltic Sea are presented. The full system including the mission planning interface, behavior tree, controllers, dead-reckoning and object detection algorithm is validated. The submerged target is successfully detected both in simulation and reality, and simulation tools show tight integration with target hardware.
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| 4. |
- Bhat, Sriharsha, et al.
(författare)
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A Cyber-Physical System for Hydrobatic AUVs: System Integration and Field Demonstration
- 2020
-
Konferensbidrag (refereegranskat)abstract
- Cyber-physical systems (CPSs) comprise a network of sensors and actuators that are integrated with a computing and communication core. Hydrobatic Autonomous Underwater Vehicles (AUVs) can be efficient and agile, offering new use cases in ocean production, environmental sensing and security. In this paper, a CPS concept for hydrobatic AUVs is validated in real-world field trials with the hydrobatic AUV SAM developed at the Swedish Maritime Robotics Center (SMaRC). We present system integration of hardware systems, software subsystems for mission planning using Neptus, mission execution using behavior trees, flight and trim control, navigation and dead reckoning. Together with the software systems, we show simulation environments in Simulink and Stonefish for virtual validation of the entire CPS. Extensive field validation of the different components of the CPS has been performed. Results of a field demonstration scenario involving the search and inspection of a submerged Mini Cooper using payload cameras on SAM in the Baltic Sea are presented. The full system including the mission planning interface, behavior tree, controllers, dead-reckoning and object detection algorithm is validated. The submerged target is successfully detected both in simulation and reality, and simulation tools show tight integration with target hardware.
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| 5. |
- Båberg, Fredrik
(författare)
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Improving Manipulation and Control of Search and Rescue UGVs Operating Across Autonomy Levels
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Robots are often used for “dirty, dull and dangerous” jobs, where time, money or lives can be saved. A field with dangerous situations is search and rescue, with structural collapses and toxic environment. In those situations, robots have the potential to save lives.In this thesis we discuss improvements to unmanned ground vehicles (UGVs) for search and rescue in terms of manipulation and control. From the use of developments in video games for teleoperation, presentation of signal strength prediction, to ideas from 3D CAD for inspection tasks, and finally formation keeping for mobile manipulators. The problems will be addressed at different autonomy levels, regarding the robot operator interaction.We first consider teleoperation of an unmanned ground vehicle. Through a user study we compare two control modes, the traditional Tank Control and the video game inspired Free Look Control. Then, knowing how important connectivity is for teleoperation, where low connectivity can lead to the robot being abandoned, we propose a user interface which combines predicted radio signal strength with Free Look Control.Next we consider teleoperation of a mobile manipulator, which allows for inspection tasks. This adds complexity to the operator in terms of control, where not only the platform itself, but also the manipulator, has to be controlled. Inspired by 3D CAD software, where a core functionality is inspection of an object, we propose the control method Orbit Control. The system can assist with controlling some degrees of freedom of the robot, while the operator focuses on the final inspection and interaction.Finally, we consider a group of mobile manipulators transporting a larger object in a high obstacle density environment. A partially collapsed structure can contain areas which are not suitable to move in. To find a path for navigation, moving information while avoiding obstacles, can be challenging. We propose a combination of rapidly-exploring random tree (RRT) and constraint based programming, leading to a more efficient approach at high obstacle densities.
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| 6. |
- Iovino, Matteo, et al.
(författare)
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A survey of Behavior Trees in robotics and AI
- 2022
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Ingår i: Robotics and Autonomous Systems. - : Elsevier BV. - 0921-8890 .- 1872-793X. ; 154
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Tidskriftsartikel (refereegranskat)abstract
- Behavior Trees (BTs) were invented as a tool to enable modular AI in computer games, but have received an increasing amount of attention in the robotics community in the last decade. With rising demands on agent AI complexity, game programmers found that the Finite State Machines (FSM) that they used scaled poorly and were difficult to extend, adapt and reuse. In BTs, the state transition logic is not dispersed across the individual states, but organized in a hierarchical tree structure, with the states as leaves. This has a significant effect on modularity, which in turn simplifies both synthesis and analysis by humans and algorithms alike. These advantages are needed not only in game AI design, but also in robotics, as is evident from the research being done. In this paper we present a comprehensive survey of the topic of BTs in Artificial Intelligence and Robotic applications. The existing literature is described and categorized based on methods, application areas and contributions, and the paper is concluded with a list of open research challenges.
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| 7. |
- Kartasev, Mart, et al.
(författare)
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Improving the Performance of Backward Chained Behavior Trees that use Reinforcement Learning
- 2023
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Ingår i: 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1572-1579
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Konferensbidrag (refereegranskat)abstract
- In this paper we show how to improve the performance of backward chained behavior trees (BTs) that include policies trained with reinforcement learning (RL). BTs represent a hierarchical and modular way of combining control policies into higher level control policies. Backward chaining is a design principle for the construction of BTs that combines reactivity with goal directed actions in a structured way. The backward chained structure has also enabled convergence proofs for BTs, identifying a set of local conditions to be satisfied for the convergence of all trajectories to a set of desired goal states. The key idea of this paper is to improve performance of backward chained BTs by using the conditions identified in a theoretical convergence proof to configure the RL problems for individual controllers. Specifically, previous analysis identified so-called active constraint conditions (ACCs), that should not be violated in order to avoid having to return to work on previously achieved subgoals. We propose a way to set up the RL problems, such that they do not only achieve each immediate subgoal, but also avoid violating the identified ACCs. The resulting performance improvement depends on how often ACC violations occurred before the change, and how much effort, in terms of execution time, was needed to re-achieve them. The proposed approach is illustrated in a dynamic simulation environment.
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| 8. |
- Kartasev, Mart, et al.
(författare)
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Improving the Performance of Learned Controllers in Behavior Trees Using Value Function Estimates at Switching Boundaries
- 2024
-
Ingår i: IEEE Robotics and Automation Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 2377-3766. ; 9:5, s. 4647-4654
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Tidskriftsartikel (refereegranskat)abstract
- Behavior trees offer a modular approach to developing an overall controller from a set of sub-controllers that solve different sub-problems. These sub-controllers can be created using various methods, such as classical model-based control or reinforcement learning (RL). To achieve the overall goal, each sub-controller must satisfy the preconditions of the next sub-controller. Although every sub-controller may be locally optimal in achieving the preconditions of the next one, given some performance metric like completion time, the overall controller may still not be optimal with respect to the same performance metric. In this paper, we demonstrate how the performance of the overall controller can be improved if we use approximations of value functions to inform the design of a sub-controller of the needs of the next controller. We also show how, under certain assumptions, this leads to a globally optimal controller when the process is executed on all sub-controllers. Finally, this result also holds when some of the sub-controllers are already given. This means that if we are constrained to use some existing sub-controllers, the overall controller will be globally optimal, given this constraint.
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| 9. |
- Kilbo Edlund, Karl, et al.
(författare)
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Long-term ambient air pollution and coronary atherosclerosis : results from the Swedish SCAPIS study
- 2024
-
Ingår i: Atherosclerosis. - : Elsevier. - 0021-9150 .- 1879-1484.
-
Tidskriftsartikel (refereegranskat)abstract
- Background and aims: Despite firm evidence for an association between long-term ambient air pollution exposure and cardiovascular morbidity and mortality, results from epidemiological studies on the association between air pollution exposure and atherosclerosis have not been consistent. We investigated associations between long-term low-level air pollution exposure and coronary atherosclerosis.Methods: We performed a cross-sectional analysis in the large Swedish CArdioPulmonary bioImaging Study (SCAPIS, n = 30 154), a random general population sample. Concentrations of total and locally emitted particulate matter <2.5 μm (PM2.5), <10 μm (PM10), and nitrogen oxides (NOx) at the residential address were modelled using high-resolution dispersion models. We estimated associations between air pollution exposures and segment involvement score (SIS), coronary artery calcification score (CACS), number of non-calcified plaques (NCP), and number of significant stenoses, using ordinal regression models extensively adjusted for potential confounders.Results: Median 10-year average PM2.5 exposure was 6.2 μg/m3 (range 3.5–13.4 μg/m3). 51 % of participants were women and 51 % were never-smokers. None of the assessed pollutants were associated with a higher SIS or CACS. Exposure to PM2.5 was associated with NCP (adjusted OR 1.34, 95 % CI 1.13, 1.58, per 2.05 μg/m3). Associations with significant stenoses were inconsistent.Conclusions: In this large, middle-aged general population sample with low exposure levels, air pollution was not associated with measures of total burden of coronary atherosclerosis. However, PM2.5 appeared to be associated with a higher prevalence of non-calcified plaques. The results suggest that increased risk of early-stage atherosclerosis or rupture, but not increased total atherosclerotic burden, may be a pathway for long-term air pollution effects on cardiovascular disease.
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| 10. |
- Kilbo Edlund, Karl, et al.
(författare)
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Long-term ambient air pollution and coronary atherosclerosis: Results from the Swedish SCAPIS study.
- 2024
-
Ingår i: Atherosclerosis. - 1879-1484.
-
Tidskriftsartikel (refereegranskat)abstract
- Despite firm evidence for an association between long-term ambient air pollution exposure and cardiovascular morbidity and mortality, results from epidemiological studies on the association between air pollution exposure and atherosclerosis have not been consistent. We investigated associations between long-term low-level air pollution exposure and coronary atherosclerosis.We performed a cross-sectional analysis in the large Swedish CArdioPulmonary bioImaging Study (SCAPIS, n=30154), a random general population sample. Concentrations of total and locally emitted particulate matter <2.5μm (PM2.5), <10μm (PM10), and nitrogen oxides (NOx) at the residential address were modelled using high-resolution dispersion models. We estimated associations between air pollution exposures and segment involvement score (SIS), coronary artery calcification score (CACS), number of non-calcified plaques (NCP), and number of significant stenoses, using ordinal regression models extensively adjusted for potential confounders.Median 10-year average PM2.5 exposure was 6.2μg/m3 (range 3.5-13.4μg/m3). 51% of participants were women and 51% were never-smokers. None of the assessed pollutants were associated with a higher SIS or CACS. Exposure to PM2.5 was associated with NCP (adjusted OR 1.34, 95% CI 1.13, 1.58, per 2.05μg/m3). Associations with significant stenoses were inconsistent.In this large, middle-aged general population sample with low exposure levels, air pollution was not associated with measures of total burden of coronary atherosclerosis. However, PM2.5 appeared to be associated with a higher prevalence of non-calcified plaques. The results suggest that increased risk of early-stage atherosclerosis or rupture, but not increased total atherosclerotic burden, may be a pathway for long-term air pollution effects on cardiovascular disease.
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| 11. |
- Nimara, Doumitrou Daniil, et al.
(författare)
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Model-Based Reinforcement Learning for Cavity Filter Tuning
- 2023
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Ingår i: Proceedings of the 5th Annual Learning for Dynamics and Control Conference, L4DC 2023. - : ML Research Press. ; , s. 1297-1307
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Konferensbidrag (refereegranskat)abstract
- The ongoing development of telecommunication systems like 5G has led to an increase in demand of well calibrated base transceiver station (BTS) components. A pivotal component of every BTS is cavity filters, which provide a sharp frequency characteristic to select a particular band of interest and reject the rest. Unfortunately, their characteristics in combination with manufacturing tolerances make them difficult for mass production and often lead to costly manual post-production fine tuning. To address this, numerous approaches have been proposed to automate the tuning process. One particularly promising one, that has emerged in the past few years, is to use model free reinforcement learning (MFRL); however, the agents are not sample efficient. This poses a serious bottleneck, as utilising complex simulators or training with real filters is prohibitively time demanding. This work advocates for the usage of model based reinforcement learning (MBRL) and showcases how its utilisation can significantly decrease sample complexity, while maintaining similar levels of success rate. More specifically, we propose an improvement over a state-of-the-art (SoTA) MBRL algorithm, namely the Dreamer algorithm. This improvement can serve as a template for applications in other similar, high-dimensional non-image data problems. We carry experiments on two complex filter types, and show that our novel modification on the Dreamer architecture reduces sample complexity by a factor of 4 and 10, respectively. Our findings pioneer the usage of MBRL which paves the way for utilising more precise and accurate simulators which was previously prohibitively time demanding.
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| 12. |
- Pallin, Martin, et al.
(författare)
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A Decentralized Asynchronous Collaborative Genetic Algorithm for Heterogeneous Multi-agent Search and Rescue Problems
- 2021
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Ingår i: 2021 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2021. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- In this paper we propose a version of the Genetic Algorithm (GA) for combined task assignment and path planning that is highly decentralized in the sense that each agent only knows its own capabilities and data, and a set of so-called handover values communicated to it from the other agents over an unreliable low bandwidth communication channel. These handover values are used in combination with a local GA involving no other agents, to decide what tasks to execute, and what tasks to leave to others. We compare the performance of our approach to a centralized version of GA, and a partly decentralized version of GA where computations are local, but all agents need complete information regarding all other agents, including position, range, battery, and local obstacle maps. We compare solution performance as well as messages sent for the three algorithms, and conclude that the proposed algorithms has a small decrease in performance, but a significant decrease in required communication. We compare the performance of our approach to a centralized version of GA, and a partly decentralized version of GA where computations are local, but all agents need complete information regarding all other agents, including position, range, battery, and local obstacle maps. We compare solution performance as well as messages sent for the three algorithms, and conclude that the proposed algorithms has a small decrease in performance, but a significant decrease in required communication. We compare solution performance as well as messages sent for the three algorithms, and conclude that the proposed algorithms has a small decrease in performance, but a significant decrease in required communication.
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| 13. |
- Pallin, Martin, et al.
(författare)
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Formulation and Solution of the Multi-agent Concurrent Search and Rescue Problem
- 2021
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Ingår i: IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2021. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 27-33
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Konferensbidrag (refereegranskat)abstract
- In this paper we formulate and solve the concurrent multi-agent search and rescue problem (C-SARP), where a multi-agent system is to concurrently search an area and assist the victims found during the search. It is widely believed that a UAV-system can help saving lives by locating and assisting victims over large inaccessible areas in the initial stages after a disaster, such as an earthquake, flood, or plane crash. In such a scenario, a natural objective is to minimize the loss of lives. Therefore, two types of uncertainties needs to be taken into account, the uncertainty in position of the victims, and the uncertainty in health over time. It is rational to start looking where victims are most likely to be found, such as the reported position of a victim in a life boat with access to a radio, but it is also rational to start looking where loss of lives is most likely to occur, such as the uncertain position of victims swimming in cold water. We show that the proposed C-SARP is NP-hard, and that the two elements of search and rescue should not be decoupled, making C-SARP substantially different from previously studied multi agent problems, including coverage, multi agent travelling salesmen problems and earlier studies of decoupled search and rescue. Finally, we provide an experimental comparison between the most promising algorithms used in the literature to address similar problems, and find that the solutions to the C-SARP reproduce the trajectories recommended in search and rescue manuals for simple problems, but outperform those trajectories in terms of expected survivability for more complex scenarios.
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| 14. |
- Parasuraman, Ramviyas, et al.
(författare)
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Rapid prediction of network quality in mobile robots
- 2023
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Ingår i: Ad hoc networks. - : Elsevier BV. - 1570-8705 .- 1570-8713. ; 138
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Tidskriftsartikel (refereegranskat)abstract
- Mobile robots rely on wireless networks for sharing sensor data from remote missions. The robot's spatial network quality will vary considerably across a given mission environment and network access point (AP) location, which are often unknown apriori. Therefore, predicting these spatial variations becomes essential and challenging, especially in dynamic and unstructured environments. To address this challenge, we propose an online algorithm to predict wireless connection quality measured through the well-exploited Radio Signal Strength (RSS) metric in the future positions along a mobile robot's trajectory. We assume no knowledge of the environment or AP positions other than robot odometry and RSS measurements at the previous trajectory points. We propose a discrete Kalman filter-based solution considering path loss and shadowing effects. The algorithm is evaluated with unique real-world datasets in indoor, outdoor, and underground data showing prediction accuracy of up to 96%, revealing significant performance improvements over conventional approaches, including Gaussian Processes Regression. Having such accurate predictions will help the robot plan its trajectory and task operations in a communication-aware manner ensuring mission success. Further, we extensively analyze the approach regarding the impacts of localization error, source location, mobility, antenna type, and connection failures on prediction accuracy, providing novel perspectives and observations for performance evaluation.
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| 15. |
- Pyko, Andrei, et al.
(författare)
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Long-Term Exposure to Transportation Noise and Ischemic Heart Disease: A Pooled Analysis of Nine Scandinavian Cohorts.
- 2023
-
Ingår i: Environmental health perspectives. - : Environmental Health Perspectives. - 1552-9924 .- 0091-6765. ; 131:1
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Tidskriftsartikel (refereegranskat)abstract
- Transportation noise may induce cardiovascular disease, but the public health implications are unclear.The study aimed to assess exposure-response relationships for different transportation noise sources and ischemic heart disease (IHD), including subtypes.Pooled analyses were performed of nine cohorts from Denmark and Sweden, together including 132,801 subjects. Time-weighted long-term exposure to road, railway, and aircraft noise, as well as air pollution, was estimated based on residential histories. Hazard ratios (HRs) were calculated using Cox proportional hazards models following adjustment for lifestyle and socioeconomic risk factors.A total of 22,459 incident cases of IHD were identified during follow-up from national patient and mortality registers, including 7,682 cases of myocardial infarction. The adjusted HR for IHD was 1.03 [95% confidence interval (CI) 1.00, 1.05] per 10 dB Lden for both road and railway noise exposure during 5 y prior to the event. Higher risks were indicated for IHD excluding angina pectoris cases, with HRs of 1.06 (95% CI: 1.03, 1.08) and 1.05 (95% CI: 1.01, 1.08) per 10 dB Lden for road and railway noise, respectively. Corresponding HRs for myocardial infarction were 1.02 (95% CI: 0.99, 1.05) and 1.04 (95% CI: 0.99, 1.08). Increased risks were observed for aircraft noise but without clear exposure-response relations. A threshold at around 55 dB Lden was suggested in the exposure-response relation for road traffic noise and IHD.Exposure to road, railway, and aircraft noise in the prior 5 y was associated with an increased risk of IHD, particularly after exclusion of angina pectoris cases, which are less well identified in the registries. https://doi.org/10.1289/EHP10745.
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| 16. |
- Roswall, Nina, et al.
(författare)
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Long-term exposure to traffic noise and risk of incident colon cancer : A pooled study of eleven Nordic cohorts
- 2023
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Ingår i: Environmental Research. - : Elsevier BV. - 0013-9351 .- 1096-0953. ; 224
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundColon cancer incidence is rising globally, and factors pertaining to urbanization have been proposed involved in this development. Traffic noise may increase colon cancer risk by causing sleep disturbance and stress, thereby inducing known colon cancer risk-factors, e.g. obesity, diabetes, physical inactivity, and alcohol consumption, but few studies have examined this.ObjectivesThe objective of this study was to investigate the association between traffic noise and colon cancer (all, proximal, distal) in a pooled population of 11 Nordic cohorts, totaling 155,203 persons.MethodsWe identified residential address history and estimated road, railway, and aircraft noise, as well as air pollution, for all addresses, using similar exposure models across cohorts. Colon cancer cases were identified through national registries. We analyzed data using Cox Proportional Hazards Models, adjusting main models for harmonized sociodemographic and lifestyle data.ResultsDuring follow-up (median 18.8 years), 2757 colon cancer cases developed. We found a hazard ratio (HR) of 1.05 (95% confidence interval (CI): 0.99–1.10) per 10-dB higher 5-year mean time-weighted road traffic noise. In sub-type analyses, the association seemed confined to distal colon cancer: HR 1.06 (95% CI: 0.98–1.14). Railway and aircraft noise was not associated with colon cancer, albeit there was some indication in sub-type analyses that railway noise may also be associated with distal colon cancer. In interaction-analyses, the association between road traffic noise and colon cancer was strongest among obese persons and those with high NO2-exposure.DiscussionA prominent study strength is the large population with harmonized data across eleven cohorts, and the complete address-history during follow-up. However, each cohort estimated noise independently, and only at the most exposed façade, which may introduce exposure misclassification. Despite this, the results of this pooled study suggest that traffic noise may be a risk factor for colon cancer, especially of distal origin.
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| 17. |
- Roswall, Nina, et al.
(författare)
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Long-Term Exposure to Transportation Noise and Risk of Incident Stroke : A Pooled Study of Nine Scandinavian Cohorts
- 2021
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Ingår i: Journal of Environmental Health Perspectives. - : National Institute of Environmental Health Sciences (NIEHS). - 0091-6765 .- 1552-9924. ; 129:10
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Tidskriftsartikel (refereegranskat)abstract
- Background: Transportation noise is increasingly acknowledged as a cardiovascular risk factor, but the evidence base for an association with stroke is sparse.Objective: We aimed to investigate the association between transportation noise and stroke incidence in a large Scandinavian population.Methods: We harmonized and pooled data from nine Scandinavian cohorts (seven Swedish, two Danish), totaling 135,951 participants. We identified residential address history and estimated road, railway, and aircraft noise for all addresses. Information on stroke incidence was acquired through linkage to national patient and mortality registries. We analyzed data using Cox proportional hazards models, including socioeconomic and lifestyle confounders, and air pollution.Results: During follow-up (median=19.5y), 11,056 stroke cases were identified. Road traffic noise (Lden) was associated with risk of stroke, with a hazard ratio (HR) of 1.06 [95% confidence interval (CI): 1.03, 1.08] per 10-dB higher 5-y mean time-weighted exposure in analyses adjusted for individual- and area-level socioeconomic covariates. The association was approximately linear and persisted after adjustment for air pollution [particulate matter (PM) with an aerodynamic diameter of ≤2.5μm (PM2.5) and NO2]. Stroke was associated with moderate levels of 5-y aircraft noise exposure (40–50 vs. ≤40 dB) (HR=1.12; 95% CI: 0.99, 1.27), but not with higher exposure (≥50 dB, HR=0.94HR; 95% CI: 0.79, 1.11). Railway noise was not associated with stroke.Discussion: In this pooled study, road traffic noise was associated with a higher risk of stroke. This finding supports road traffic noise as an important cardiovascular risk factor that should be included when estimating the burden of disease due to traffic noise.
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| 18. |
- Scukins, Edvards, et al.
(författare)
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Deep Learning Based Situation Awareness for Multiple Missiles Evasion
- 2024
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Ingår i: 2024 International Conference on Unmanned Aircraft Systems, ICUAS 2024. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1446-1452
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Konferensbidrag (refereegranskat)abstract
- As the effective range of air-to-air missiles increases, it becomes harder for pilots and Unmanned aerial vehicle (UAV) operators to maintain the Situational Awareness (SA) needed to keep their aircraft safe. In this work, we propose a decision support tool to help pilots in Beyond Visual Range (BVR) air combat scenarios assess the risks of different options and make decisions based on those. Building upon earlier research that primarily addressed the threat of a single missile, we extend these ideas to encompass the complex scenario of multiple missile threats. The proposed method uses Deep Neural Networks (DNN) to learn from high-fidelity simulations and provide the pilots with an outcome estimate for a set of different strategies. Our results demonstrate that the proposed system can manage multiple incoming missiles, evaluate a family of options, and recommend the least risky course of action while accounting for all incoming air-to-air threats.
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| 19. |
- Scukins, Edvards, et al.
(författare)
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Enhancing Situation Awareness in Beyond Visual Range Air Combat with Reinforcement Learning-based Decision Support
- 2023
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Ingår i: 2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 56-62
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Konferensbidrag (refereegranskat)abstract
- Military aircraft pilots need to adjust to a constantly changing battlefield. A system that aids in understanding challenging combat circumstances and suggests appropriate responses can considerably improve the effectiveness of pilots. In this paper, we provide a Reinforcement Learning (RL) based system that acts as an aid in determining if an afterburner should be turned on to escape an incoming air-to-air missile. An afterburner is a component of a jet engine that increases thrust at the expense of exceptionally high fuel consumption. Thus it provides a short-term advantage, at the cost of a longterm disadvantage, in terms of reduced mission time. Helping to choose when to use the afterburner may significantly lengthen the flight duration, allowing aircraft to support friendly aircraft for longer and suffer fewer friendly fatalities due to this extended ability to provide support. We propose an RL-based risk estimation approach to help determine whether additional thrust is required to escape an incoming missile and study the benefits of thrust-aided evasive maneuvers. The suggested technique gives pilots a risk estimate for the scenario and a recommended course of action. We create an environment in which a pilot must decide whether or not to activate additional thrust to achieve the intended aim at a potentially high fuel consumption cost. Additionally, we investigate various trade-offs of the generated evasive maneuver policies.
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| 20. |
- Scukins, Edvards, et al.
(författare)
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Monte Carlo Tree Search and Convex Optimization for Decision Support in Beyond-Visual-Range Air Combat
- 2023
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Ingår i: 2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 48-55
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Konferensbidrag (refereegranskat)abstract
- Air combat is a high-risk activity where pilots must be aware of the surrounding situation to outperform the opposing team. The chances of beating the opposing team improve when the pilots have superior situation awareness, thus allowing them to act before the opposing team can do counteractions. In a highly dynamic environment, such as air combat, it can be difficult for pilots to track all adversarial units and their capabilities. In this work, we propose a combination of Monte Carlo Tree Search (MCTS) and Convex optimization to help pilots analyze the situation and be aware of any potential risks associated with missile guidance in Beyond Visual Range air combat. Our process uses MCTS to assess the best action from an opposing aircraft perspective. At the same time, the convex optimization problem searches available aircraft trajectories that enable missile guidance in relation to the opponent's potential actions. The proposed system is intended to support human decisions made by a pilot inside the aircraft or by a remote pilot operating an unmanned aerial system (UAS).
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| 21. |
- Scukins, Edvards, et al.
(författare)
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Using Reinforcement Learning to Create Control Barrier Functions for Explicit Risk Mitigation in Adversarial Environments
- 2021
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Ingår i: 2021 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE Robotics and Automation Society.
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Konferensbidrag (refereegranskat)abstract
- Air Combat is a high-risk activity carried out by trained professionals operating sophisticated equipment. During this activity, a number of trade-offs have to be made, such as the balance between risk and efficiency. A policy that minimizes risk could have very low efficiency, and one that maximizes efficiency may involve very high risk.In this study, we use Reinforcement Learning (RL) to create Control Barrier Functions (CBF) that captures the current risk, in terms of worst-case future separation between the aircraft and an enemy missile.CBFs are usually designed manually as closed-form expressions, but for a complex system such as a guided missile, this is not possible. Instead, we solve an RL problem using high fidelity simulation models to find value functions with CBF properties, that can then be used to guarantee safety in real air combat situations. We also provide a theoretical analysis of what family of RL problems result in value functions that can be used as CBFs in this way.The proposed approach allows the pilot in an air combat scenario to set the exposure level deemed acceptable and continuously monitor the risk related to his/her own safety. Given input regarding acceptable risk, the system limits the choices of the pilot to those that guarantee future satisfaction of the provided bound.
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| 22. |
- Sprague, Christopher, et al.
(författare)
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Adding Neural Network Controllers to Behavior Trees without Destroying Performance Guarantees
- 2022
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Ingår i: The 61th IEEE Conference on Decision and Control (CDC 2022). - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- In this paper, we show how Behavior Trees that have performance guarantees, in terms of safety and goal convergence, can be extended with components that were designed using machine learning, without destroying those performance guarantees. Machine learning approaches such as reinforcement learning or learning from demonstration can be very appealing to AI designers that want efficient and realistic behaviors in their agents. However, those algorithms seldom provide guarantees for solving the given task in all different situations while keeping the agent safe. Instead, such guarantees are often easier to find for manually designed model-based approaches. In this paper we exploit the modularity of behavior trees to extend a given design with an efficient, but possibly unreliable, machine learning component in a way that preserves the guarantees. The approach is illustrated with an inverted pendulum example.
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| 23. |
- Sprague, Christopher, et al.
(författare)
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Continuous-Time Behavior Trees as Discontinuous Dynamical Systems
- 2022
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Ingår i: IEEE Control Systems Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 2475-1456. ; 6, s. 1891-1896
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Tidskriftsartikel (refereegranskat)abstract
- Behavior trees represent a hierarchical and modular way of combining several low-level control policies into a high-level task-switching policy. Hybrid dynamical systems can also be seen in terms of task switching between different policies, and therefore several comparisons between behavior trees and hybrid dynamical systems have been made, but only informally, and only in discrete time. A formal continuous-time formulation of behavior trees has been lacking. Additionally, convergence analyses of specific classes of behavior tree designs have been made, but not for general designs. In this letter, we provide the first continuous-time formulation of behavior trees, show that they can be seen as discontinuous dynamical systems (a subclass of hybrid dynamical systems), which enables the application of existence and uniqueness results to behavior trees, and finally, provide sufficient conditions under which such systems will converge to a desired region of the state space for general designs. With these results, a large body of results on continuous-time dynamical systems can be brought to use when designing behavior tree controllers.
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| 24. |
- Sprague, Christopher
(författare)
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Efficient and Trustworthy Artificial Intelligence for Critical Robotic Systems
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Critical robotic systems are systems whose functioning is critical to both ensuring the accomplishment of a given mission and preventing the endangerment of life and the surrounding environment. These critical aspects can be formally captured by convergence, in the sense that the system's state goes to a desired region of the statespace, and safety, in the sense that the system's state avoids unsafe regions of the statespace. Data-driven control policies, found through e.g. imitation learning or reinforcement learning, can outperform model-based methods in achieving convergence and safety efficiently; however, they often only do so by encouraging them, thus, they can be difficult to trust. Model-based control policies, on the other hand, are often well-suited to admitting formal guarantees of convergence and safety, thus they are often easier to trust. The main question asked in this thesis is: how can we compose data-driven and model-based control policies together to encourage efficiency while, at the same time, formally guaranteeing convergence and safety?We answer this question with behaviour trees, a framework to represent hybrid control systems in a modular way. We present the first formal definition of behaviour trees as a hybrid system and present the conditions under which the execution of any behaviour tree as a hybrid control system will formally guarantee convergence and safety. Moreover, we present the conditions under which such formal guarantees can be maintained when including unguaranteed data-driven control policies, such as those coming from imitation learning or reinforcement learning. We also present an approach to synthesise such data-driven control policies in such a way that they encourage convergence and safety by adapting to unforeseen events. Alongside the above, we also explore an ancillary aspect of robot autonomy by improving the efficiency of simultaneous localisation and mapping through imitation learning. Lastly, we validate the advantages of behaviour trees' modularity in a real-world autonomous underwater vehicle's control system, and argue that this modularity contributes to efficiency, in terms of ease of use, and trust, in terms of facilitating human understanding.
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| 25. |
- Sprague, Christopher, et al.
(författare)
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Learning Dynamic-Objective Policies from a Class of Optimal Trajectories
- 2020
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - : Institute of Electrical and Electronics Engineers Inc.. ; , s. 597-602
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Konferensbidrag (refereegranskat)abstract
- Optimal state-feedback controllers, capable of changing between different objective functions, are advantageous to systems in which unexpected situations may arise. However, synthesising such controllers, even for a single objective, is a demanding process. In this paper, we present a novel and straightforward approach to synthesising these policies through a combination of trajectory optimisation, homotopy continuation, and imitation learning. We use numerical continuation to efficiently generate optimal demonstrations across several objectives and boundary conditions, and use these to train our policies. Additionally, we demonstrate the ability of our policies to effectively learn families of optimal state- feedback controllers, which can be used to change objective functions online. We illustrate this approach across two trajectory optimisation problems, an inverted pendulum swingup and a spacecraft orbit transfer, and show that the synthesised policies, when evaluated in simulation, produce trajectories that are near-optimal. These results indicate the benefit of trajectory optimisation and homotopy continuation to the synthesis of controllers in dynamic-objective contexts.
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| 26. |
- Sprague, Christopher, et al.
(författare)
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Learning How to Learn Bathymetry
- 2020
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Ingår i: 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020. - : Institute of Electrical and Electronics Engineers Inc..
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Konferensbidrag (refereegranskat)abstract
- In this work, we investigate using reinforcement learning (RL) to learn controllers that generate continuous trajectories that minimise the uncertainty of a bathymetric model of a given environment, whilst respecting time constraints.
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| 27. |
- Thacher, Jesse D., et al.
(författare)
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Exposure to long-term source-specific transportation noise and incident breast cancer : A pooled study of eight Nordic cohorts
- 2023
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Ingår i: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 178
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Tidskriftsartikel (refereegranskat)abstract
- Background: Environmental noise is an important environmental exposure that can affect health. An association between transportation noise and breast cancer incidence has been suggested, although current evidence is limited. We investigated the pooled association between long-term exposure to transportation noise and breast cancer incidence.Methods: Pooled data from eight Nordic cohorts provided a study population of 111,492 women. Road, railway, and aircraft noise were modelled at residential addresses. Breast cancer incidence (all, estrogen receptor (ER) positive, and ER negative) was derived from cancer registries. Hazard ratios (HR) were estimated using Cox Proportional Hazards Models, adjusting main models for sociodemographic and lifestyle variables together with long-term exposure to air pollution.Results: A total of 93,859 women were included in the analyses, of whom 5,875 developed breast cancer. The median (5th–95th percentile) 5-year residential road traffic noise was 54.8 (40.0–67.8) dB Lden, and among those exposed, the median railway noise was 51.0 (41.2–65.8) dB Lden. We observed a pooled HR for breast cancer (95 % confidence interval (CI)) of 1.03 (0.99–1.06) per 10 dB increase in 5-year mean exposure to road traffic noise, and 1.03 (95 % CI: 0.96–1.11) for railway noise, after adjustment for lifestyle and sociodemographic covariates. HRs remained unchanged in analyses with further adjustment for PM2.5 and attenuated when adjusted for NO2 (HRs from 1.02 to 1.01), in analyses using the same sample. For aircraft noise, no association was observed. The associations did not vary by ER status for any noise source. In analyses using <60 dB as a cutoff, we found HRs of 1.08 (0.99–1.18) for road traffic and 1.19 (0.95–1.49) for railway noise.Conclusions: We found weak associations between road and railway noise and breast cancer risk. More high-quality prospective studies are needed, particularly among those exposed to railway and aircraft noise before conclusions regarding noise as a risk factor for breast cancer can be made.
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| 28. |
- Ögren, Petter, 1974-, et al.
(författare)
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Behavior Trees in Robot Control Systems
- 2022
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Ingår i: Annual Review of Control, Robotics, and Autonomous Systems. - : Annual Reviews. - 2573-5144 .- 2573-5144. ; 5:1, s. 81-107
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we provide a control-theoretic perspective on the research area of behavior trees in robotics. The key idea underlying behavior trees is to make use of modularity, hierarchies, and feedback in order to handle the complexity of a versatile robot control system. Modularity is a well-known tool to handle software complexity by enabling the development, debugging, and extension of separate modules without detailed knowledge of the entire system. A hierarchy of such modules is natural, since robot tasks can often be decomposed into a hierarchy of subtasks. Finally, feedback control is a fundamental tool for handling uncertainties and disturbances in any low-level control system, but in order to enable feedback control on the higher level, where one module decides what submodule to execute, information regarding the progress and applicability of each submodule needs to be shared in the module interfaces. We describe how these three concepts can be used in theoretical analysis, practical design, and extensions and combinations with other ideas from control theory and robotics.
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| 29. |
- Ögren, Petter, 1974-
(författare)
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Convergence Analysis of Hybrid Control Systems in the Form of Backward Chained Behavior Trees
- 2020
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Ingår i: IEEE Robotics and Automation Letters. - : IEEE Robotics and Automation Society. - 2377-3766.
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Tidskriftsartikel (refereegranskat)abstract
- A robot control system is often composed of a set of low level continuous controllers and a switching policy that decides which of those continuous controllers to apply at each time instant. The switching policy can be either a Finite State Machine (FSM), a Behavior Tree (BT) or some other structure. In previous work we have shown how to create BTs using a backward chained approach that results in a reactive goal directed policy. This policy can be thought of as providing disturbance rejection at the task level in the sense that if a disturbance changes the state in such a way that the currently running continuous controller cannot handle it, the policy will switch to the appropriate continuous controller. In this letter we show how to provide convergence guarantees for such policies.
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| 30. |
- Ögren, Petter, 1974-, et al.
(författare)
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Creating Trustworthy AI for UAS using Labeled Backchained Behavior Trees
- 2023
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Ingår i: 2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1029-1036
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Konferensbidrag (refereegranskat)abstract
- Unmanned Aerial Systems (UAS) have the potential to provide cost effective solutions to many problems, but their control systems need to be safe and trustworthy in order to realize this potential. In this paper we show how behavior trees (BTs), created using backward chaining and using a particular way of labelling subtrees, can be used to meet the requirements of trustworthy autonomy described in a US air force (USAF) report. Behavior Trees represent a modular, reactive and transparent way of structuring a control system that is receiving increasing interest in the UAS community. While their safety and efficiency have been investigated in prior research, their connection to trustworthy autonomy has not been explored. A set of guidelines for trustworthy autonomy, taken from a USAF report, include items such as: being similar to how humans parse problems, being able to explain its reasoning in a concise way, and being able to be visualized at different levels of resolution. We propose a new way of deriving explanations that conform to these guidelines, using a particular labeling of subtrees in the BT combined with a structured design methodology called backward chaining. The proposed approach is illustrated in a detailed example.
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| 31. |
- Özkahraman, Özer, 1992-, et al.
(författare)
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Collaborative Navigation-Aware Coverage in Feature-Poor Environments
- 2022
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Ingår i: International Conference on Intelligent Robots and Systems (IROS), 2022.
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Konferensbidrag (refereegranskat)abstract
- Multi agent coverage and robot navigation are two very important research fields within robotics. However, their intersection has received limited attention. In multi agent coverage, perfect navigation is often assumed, and in robot navigation, the focus is often to minimize the localization error with the aid of stationary features from the environment.The need for integration of the two becomes clear in environments with very sparse features or landmarks, for example when a group of Autonomous Underwater Vehicles (AUVs) are to search a uniform seafloor for mines or other dangerous objects.In such environments, localization systems are often deprived of detectable features to use that could increase their accuracy.In this paper we propose an algorithm for doing navigation aware multi agent coverage in areas with no landmarks.Instead of using identical lawn mower patterns, we propose to mirror every other pattern to enable the agents to meet up and makeinter-agent measurements and share information regularly. This improves performance in two ways,global drift in relation to the area to be covered is reduced, and local coverage gaps between adjacent patterns are reduced.Further, we show that this can be accomplished within the constraints of very limited sensing, computing and communication resources that most AUVs have available.The effectiveness of our method is shown through statistically significant simulated experiments.
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| 32. |
- Özkahraman, Özer, 1992-, et al.
(författare)
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Combining Control Barrier Functions and Behavior Trees for Multi-Agent Underwater Coverage Missions
- 2020
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Ingår i: Proceedings of 59th Conference on Decision and Control, 2020.
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Konferensbidrag (refereegranskat)abstract
- Robot missions typically involve a number of desired objectives, such as avoiding collisions, staying connected to other robots, gathering information using sensors and returning to the charging station before the battery runs out.Some of these objectives need to be taken into account at the same time, such as avoiding collisions and staying connected, while others are focused upon during different parts of the executions, such as returning to the charging station and connectivity maintenance.In this paper, we show how Control Barrier Functions(CBFs) and Behavior Trees(BTs) can be combined in a principled manner to achieve both types of task compositions, with performance guarantees in terms of mission completion. We illustrate our method with a simulated underwater coverage mission.
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| 33. |
- Özkahraman, Özer, 1992-, et al.
(författare)
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Data-Driven Damage Detection and Control Adaptation for an Autonomous Underwater Vehicle
- 2022
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Ingår i: 61st IEEE Conference on Decision and Control (CDC), 2022.
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Konferensbidrag (refereegranskat)abstract
- Underwater robotic exploration missions typically involve traveling long distances without any human contact.The robots that go on such missions risk getting damaged by the unknown environment, accruing great costs and missed opportunities.Thus it is important for the robot to be able to accommodate unknown changes to its dynamics as much as possible and attempt to finish the given mission, or at the very least move itself to a retrievable position.In this paper, we show how we can detect physical changes to the robot reliably (79\% on real robot data) and then incorporate these changes through adapting the model to the data followed by automated control redesign. We adopt a piecewise-affine (PWA) modelling of the dynamics that is well suited for low data regime learning of the dynamics and provides a structure for computationally efficient control synthesis.We demonstrate the effectiveness of the proposed method on a combination of real robot data and simulated scenarios.
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| 34. |
- Özkahraman, Özer, 1992-, et al.
(författare)
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Efficient Navigation Aware Seabed Coverage using AUVs
- 2021
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Ingår i: Proceedings of 2021 IEEE International Conference on Safety, Security, and Rescue Robotics (SSRR), October 25-27 2021, New York, USA..
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Konferensbidrag (refereegranskat)abstract
- Area coverage and robot navigation are two important research fields within robotics. However, their intersection has received limited attention. In coverage problems, perfect navigation is often assumed, and in robot navigation, the focus is often to minimize the localization error while traveling a given trajectory.The need for integration of the two becomes clear in environments with very sparse features or landmarks, for example when an Autonomous Underwater Vehicle (AUV) is to search the seafloor for dangerous objects, such as mines.The potential consequences of missing a mine due to navigation errors can be catastrophic.If the localization error is large, a trajectory that was designed to guarantee complete coverage might have missed significant parts of the area. Thus, the coverage trajectory must be planned with the navigation performance in mind, applying a combination of using large enough planned overlaps of sensor footprints to account for the position uncertainty, and reducing this uncertainty by re-visiting the known sparse landmarks.In this paper we compute trajectories that guarantee coverage for a given area under assumptions on worst case localization error growth.We further more compute upper bounds for how large areas can be covered using common coverage patterns and a single landmark, which leads to bounds on how sparse the landmarks can be in the regions to be covered.
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| 35. |
- Özkahraman, Özer, 1992-
(författare)
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Multi-Agent Mission Planning and Execution for Small Autonomous Underwater Vehicles
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Our planet is mostly covered in water, most of it still unexplored.In order to understand our environment better, oceanographers have been mapping and monitoring these waters using ship-mounted sensors and wired vehicles with limited range compared to the vastness of the oceans.The limited range and dependence on manned support vehicles has kept missions expensive and infrequent.To solve this problem, the sensors need to become independent of support vehicles, they need to venture into completely unexplored, unmapped regions of the seas by themselves and safely return with the data.This is where autonomous underwater vehicles (AUVs) have started to make a difference.In this thesis we investigate how multiple small AUVs can be utilized to efficiently and accurately sense very large volumes of water.Water absorbs electromagnetic radiation, meaning satellite-based global positioning systems (we will use GPS to refer to any such system), wide-angle cameras and radio communications are infeasible.These constraints ultimately result in uncertain localization of the vehicles.Furthermore, the vehicles are under constant disturbances from the water currents, fish and bio-fouling, which result in the dynamics of the vehicles being uncertain or even changing during the mission.In the first part of this thesis, we focus on the large-scale sensing problem under localization uncertainties by examining the caging and coverage problems.In the coverage problem, each AUV is uncertain about its exact position while tasked with sensing a stationary area.We show that we can still guarantee complete coverage and formulate the efficiency characteristics of different approaches.Furthermore, we show that when the vehicles are equipped with sensors and low-bandwidth communication methods, we can increase the effective range of a team of AUVs considerably by utilizing loop-closures over shared pose-graphs. In the caging problem, the localization uncertainty is focused on the entity that is being caged, its location is unknown but bounded.We show that through a combination of algorithms, the caging problem can be solved and a solution can be guaranteed, while simultaneously producing a list of specifications for the mission.In the second part, we focus on the individuals of the team and what they need to do in order for the team of AUVs to succeed.First, we identify that when there is a team of cooperative vehicles working together, conflicting goals rise.Each vehicle needs to pick between satisfying its own constraints and the constraints that come from being in a team. We propose a solution to this problem through a combination of Control Barrier Function (CBF) and Behavior Trees (BT).Secondly, we examine the possibility that a vehicle might undergo physical changes, like a broken thruster, that result in the vehicle being unable to complete the entire mission.Even in such a scenario, if the broken vehicle can still move to contact a normal one, the rest of the team can compensate through re-planning and the overall mission can still be completed.To do so, the broken vehicle must compensate for the change until a rendezvous.We propose a data-driven pipeline that can detect and plan around such a physical change within some bounds.
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| 36. |
- Özkahraman, Özer, 1992-, et al.
(författare)
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Underwater Caging and Capture for Autonomous Underwater Vehicles
- 2020
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Ingår i: Global Oceans 2020. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- In this paper, we consider the problem of caging and eventual capture of an underwater entity using multiple Autonomous Underwater Vehicles (AUVs) in a 3D water volume We solve this problem both with and without taking bathymetry into account. Our proposed algorithm for range-limited sensing in 3D environments captures a finite-speed entity based on sparse and irregular observations. After an isolated initial sighting of the entity, the uncertainty of its whereabouts grows while deployment of the AUV system is underway. To contain the entity, an initial cage, or barrier of sensing footprints, is created around the initial sighting, using islands and other terrain as part of the cage if available. After the initial cage is established, the system waits for a second sighting, and the possible opportunity to create a smaller, shrinkable cage. This process continues until at some point it is possible to create this smaller cage, resulting in capture, meaning the entity is sensed directly and continuously. We present a set of algorithms for addressing the scenario above, and illustrate their performance on a set of examples. The proposed algorithm is a combination of solutions to the min-cut problem, the set cover problem, the linear bottleneck assignment problem and the Thomson problem.
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