| 1. |
- Adolfsson, Daniel, 1992-
(författare)
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Robust large-scale mapping and localization : Combining robust sensing and introspection
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The presence of autonomous systems is rapidly increasing in society and industry. To achieve successful, efficient, and safe deployment of autonomous systems, they must be navigated by means of highly robust localization systems. Additionally, these systems need to localize accurately and efficiently in realtime under adverse environmental conditions, and within considerably diverse and new previously unseen environments.This thesis focuses on investigating methods to achieve robust large-scale localization and mapping, incorporating robustness at multiple stages. Specifically, the research explores methods with sensory robustness, utilizing radar, which exhibits tolerance to harsh weather, dust, and variations in lighting conditions. Furthermore, the thesis presents methods with algorithmic robustness, which prevent failures by incorporating introspective awareness of localization quality. This thesis aims to answer the following research questions:How can radar data be efficiently filtered and represented for robust radar odometry? How can accurate and robust odometry be achieved with radar? How can localization quality be assessed and leveraged for robust detection of localization failures? How can self-awareness of localization quality be utilized to enhance the robustness of a localization system?While addressing these research questions, this thesis makes the following contributions to large-scale localization and mapping: A method for robust and efficient radar processing and state-of-the-art odometry estimation, and a method for self-assessment of localization quality and failure detection in lidar and radar localization. Self-assessment of localization quality is integrated into robust systems for large-scale Simultaneous Localization And Mapping, and rapid global localization in prior maps. These systems leverage self-assessment of localization quality to improve performance and prevent failures in loop closure and global localization, and consequently achieve safe robot localization.The methods presented in this thesis were evaluated through comparative assessments of public benchmarks and real-world data collected from various industrial scenarios. These evaluations serve to validate the effectiveness and reliability of the proposed approaches. As a result, this research represents a significant advancement toward achieving highly robust localization capabilities with broad applicability.
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| 2. |
- Ahmed, Muhammad Rehan
(författare)
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Compliance Control of Robot Manipulator for Safe Physical Human Robot Interaction
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Inspiration from biological systems suggests that robots should demonstrate same level of capabilities that are embedded in biological systems in performing safe and successful interaction with the humans. The major challenge in physical human robot interaction tasks in anthropic environment is the safe sharing of robot work space such that robot will not cause harm or injury to the human under any operating condition.Embedding human like adaptable compliance characteristics into robot manipulators can provide safe physical human robot interaction in constrained motion tasks. In robotics, this property can be achieved by using active, passive and semi active compliant actuation devices. Traditional methods of active and passive compliance lead to complex control systems and complex mechanical design.In this thesis we present compliant robot manipulator system with semi active compliant device having magneto rheological fluid based actuation mechanism. Human like adaptable compliance is achieved by controlling the properties of the magneto rheological fluid inside joint actuator. This method offers high operational accuracy, intrinsic safety and high absorption to impacts. Safety is assured by mechanism design rather than by conventional approach based on advance control. Control schemes for implementing adaptable compliance are implemented in parallel with the robot motion control that brings much simple interaction control strategy compared to other methods.Here we address two main issues: human robot collision safety and robot motion performance.We present existing human robot collision safety standards and evaluate the proposed actuation mechanism on the basis of static and dynamic collision tests. Static collision safety analysis is based on Yamada’s safety criterion and the adaptable compliance control scheme keeps the robot in the safe region of operation. For the dynamic collision safety analysis, Yamada’s impact force criterion and head injury criterion are employed. Experimental results validate the effectiveness of our solution. In addition, the results with head injury criterion showed the need to investigate human bio-mechanics in more details in order to acquire adequate knowledge for estimating the injury severity index for robots interacting with humans.We analyzed the robot motion performance in several physical human robot interaction tasks. Three interaction scenarios are studied to simulate human robot physical contact in direct and inadvertent contact situations. Respective control disciplines for the joint actuators are designed and implemented with much simplified adaptable compliance control scheme.The series of experimental tests in direct and inadvertent contact situations validate our solution of implementing human like adaptable compliance during robot motion and prove the safe interaction with humans in anthropic domains.
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| 3. |
- Akalin, Neziha, 1988-
(författare)
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Perceived Safety in Social Human-Robot Interaction
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This compilation thesis contributes to a deeper understanding of perceived safety in human-robot interaction (HRI) with a particular focus on social robots. The current understanding of safety in HRI is mostly limited to physical safety, whereas perceived safety has often been neglected and underestimated. However, safe HRI requires a conceptualization of safety that goes beyond physical safety covering also perceived safety of the users. Within this context, this thesis provides a comprehensive analysis of perceived safety in HRI with social robots, considering a diverse set of human-related and robot-related factors.Two particular challenges for providing perceived safety in HRI are 1) understanding and evaluating human safety perception through direct and indirect measures, and 2) utilizing the measured level of perceived safety for adapting the robot behaviors. The primary contribution of this dissertation is in addressing the first challenge. The thesis investigates perceived safety in HRI by alternating between conducting user studies, literature review, and testing the findings from the literature within user studies.In this thesis, six main factors influencing perceived safety in HRI are lifted: the context of robot use, the user’s comfort, experience and familiarity with robots, trust, sense of control over the interaction, and transparent and predictable robot behaviors. These factors could provide a common understanding of perceived safety and bridge the theoretical gap in the literature. Moreover, this thesis proposes an experimental paradigm to observe and quantify perceived safety using objective and subjective measures. This contributes to bridging the methodological gap in the literature.The six factors are reviewed in HRI literature, and the robot features that affect these factors are organized in a taxonomy. Although this taxonomy focuses on social robots, the identified characteristics are relevant to other types of robots and autonomous systems. In addition to the taxonomy, the thesis provides a set of guidelines for providing perceived safety in social HRI. As a secondary contribution, the thesis presents an overview of reinforcement learning applications in social robotics as a suitable learning mechanism for adapting the robots’ behaviors to mitigate psychological harm.
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| 4. |
- Albitar, Houssam, 1975-
(författare)
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Enabling a Robot for Underwater Surface Cleaning
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Biofouling build-up on submerged structures such as ships, petroleum and gas storage tanks, electric power plants, bridges, oil rigs etc. is a major problem that affects the surface material of the structure, the eventual hydrodynamic quality of the surface and in some cases the efficacy of cooling systems. Underwater cleaning is a solution to maintain submerged structures in order to assure proper functioning for as long as possible. Consequently, there has been an increased interest in the development of new technologies for robotised underwater cleaning systems.This thesis presents a new concept of a flexible crawling mechanism for an industrial underwater cleaning robot, which is evaluated from the viewpoint of its capability to work underwater, scanning the desired surface, and perform a cleaning task. The main research questions investigated in this thesis are: (1.) how to select the most important features in choosing the platform mechanism to fulfil the surface scanning operation, (2.) how to design the platform in order to bear the forces related to the cleaning task, (3.) how to maintain surface contact throughout cleaning, (4.) determine the significant parameters to be monitored in order to ensure stable positioning on the surface during the cleaning process and (5.) how to develop the control of actuators to realise the locomotion and to follow the desired trajectory.This thesis begins with a classification and discussion of the available solutions for underwater operation, taking into consideration the benefits and drawbacks, overall efficiency and environmental and human safety issues. From this survey, an underwater mobile robotic platform is designed to address the main requirements and industrial needs. Further, a study and simulation of its mobility and stability on the surface is performed and a complete scenario of the entire cleaning operation is presented. In addition, an overview of the required sensors and the control system is given. Finally, a new robotised system was developed to clean underwater surfaces with minimum active degrees of freedom. A successful simulation and real experimental results were obtained with a simplified lab-scale prototype. The thesis concludes with a summary of future works and outlook for the growing field of underwater cleaning robots.
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| 5. |
- Alirezaie, Marjan, 1980-
(författare)
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Bridging the Semantic Gap between Sensor Data and Ontological Knowledge
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The rapid growth of sensor data can potentially enable a better awareness of the environment for humans. In this regard, interpretation of data needs to be human-understandable. For this, data interpretation may include semantic annotations that hold the meaning of numeric data. This thesis is about bridging the gap between quantitative data and qualitative knowledge to enrich the interpretation of data. There are a number of challenges which make the automation of the interpretation process non-trivial. Challenges include the complexity of sensor data, the amount of available structured knowledge and the inherent uncertainty in data. Under the premise that high level knowledge is contained in ontologies, this thesis investigates the use of current techniques in ontological knowledge representation and reasoning to confront these challenges. Our research is divided into three phases, where the focus of the first phase is on the interpretation of data for domains which are semantically poor in terms of available structured knowledge. During the second phase, we studied publicly available ontological knowledge for the task of annotating multivariate data. Our contribution in this phase is about applying a diagnostic reasoning algorithm to available ontologies. Our studies during the last phase have been focused on the design and development of a domain-independent ontological representation model equipped with a non-monotonic reasoning approach with the purpose of annotating time-series data. Our last contribution is related to coupling the OWL-DL ontology with a non-monotonic reasoner. The experimental platforms used for validation consist of a network of sensors which include gas sensors whose generated data is complex. A secondary data set includes time series medical signals representing physiological data, as well as a number of publicly available ontologies such as NCBO Bioportal repository.
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| 6. |
- Andreasson, Henrik, 1977-
(författare)
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Local visual feature based localisation and mapping by mobile robots
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis addresses the problems of registration, localisation and simultaneous localisation and mapping (SLAM), relying particularly on local visual features extracted from camera images. These fundamental problems in mobile robot navigation are tightly coupled. Localisation requires a representation of the environment (a map) and registration methods to estimate the pose of the robot relative to the map given the robot’s sensory readings. To create a map, sensor data must be accumulated into a consistent representation and therefore the pose of the robot needs to be estimated, which is again the problem of localisation. The major contributions of this thesis are new methods proposed to address the registration, localisation and SLAM problems, considering two different sensor configurations. The first part of the thesis concerns a sensor configuration consisting of an omni-directional camera and odometry, while the second part assumes a standard camera together with a 3D laser range scanner. The main difference is that the former configuration allows for a very inexpensive set-up and (considering the possibility to include visual odometry) the realisation of purely visual navigation approaches. By contrast, the second configuration was chosen to study the usefulness of colour or intensity information in connection with 3D point clouds (“coloured point clouds”), both for improved 3D resolution (“super resolution”) and approaches to the fundamental problems of navigation that exploit the complementary strengths of visual and range information. Considering the omni-directional camera/odometry setup, the first part introduces a new registration method based on a measure of image similarity. This registration method is then used to develop a localisation method, which is robust to the changes in dynamic environments, and a visual approach to metric SLAM, which does not require position estimation of local image features and thus provides a very efficient approach. The second part, which considers a standard camera together with a 3D laser range scanner, starts with the proposal and evaluation of non-iterative interpolation methods. These methods use colour information from the camera to obtain range information at the resolution of the camera image, or even with sub-pixel accuracy, from the low resolution range information provided by the range scanner. Based on the ability to determine depth values for local visual features, a new registration method is then introduced, which combines the depth of local image features and variance estimates obtained from the 3D laser range scanner to realise a vision-aided 6D registration method, which does not require an initial pose estimate. This is possible because of the discriminative power of the local image features used to determine point correspondences (data association). The vision-aided registration method is further developed into a 6D SLAM approach where the optimisation constraint is based on distances of paired local visual features. Finally, the methods introduced in the second part are combined with a novel adaptive normal distribution transform (NDT) representation of coloured 3D point clouds into a robotic difference detection system.
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| 7. |
- Arain, Muhammad Asif, 1983-
(författare)
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Efficient Remote Gas Inspection with an Autonomous Mobile Robot
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Human-caused greenhouse gas emissions are one of the major sources of global warming, which is threatening to reach a tipping point. Inspection systems that can provide direct information about critical factors causing global warming, such as systems for gas detection and location of gas sources, are urgently needed to analyze the fugitive emissions and take necessary actions.This thesis presents an autonomous robotic system capable of performing efficient exploration by selecting informative sampling positions for gas detection and gas distribution mapping – the Autonomous Remote Methane Explorer (ARMEx). In the design choice of ARMEx, a ground robot carries a spectroscopybased remote gas sensor, such as a Remote Methane Leak Detector (RMLD), that collects integral gas measurements along up to 30 m long optical-beams. The sensor is actuated to sample a large area inside an adjustable field of view, and with the mobility of the robot, adaptive sampling for high spatial resolution in the areas of interest is made possible to inspect large environments.In a typical gas sampling mission, the robot needs to localize itself and plan a traveling path to visit different locations in the area, which is a largely solved problem. However, the state-of-the-art prior to this thesis fell short of providing the capability to select informative sampling positions autonomously. This thesis introduces efficient measurement strategies to bring autonomy to mobile remote gas sensing. The strategies are based on sensor planning algorithms that minimize the number of measurements and distance traveled while optimizing the inspection criteria: full sensing coverage of the area for gas detection, and suitably overlapping sensing coverage of different viewpoints around areas of interest for gas distribution mapping.A prototype implementation of ARMEx was deployed in a large, real-world environment where inspection missions performed by the autonomous system were compared with runs teleoperated by human experts. In six experimental trials, the autonomous system created better gas maps, located more gas sources correctly, and provided better sensing coverage with fewer sensing positions than human experts.
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| 8. |
- Asadi, Sahar, 1983-
(författare)
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Towards Dense Air Quality Monitoring : Time-Dependent Statistical Gas Distribution Modelling and Sensor Planning
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis addresses the problem of gas distribution modelling for gas monitoring and gas detection. The presented research is particularly focused on the methods that are suitable for uncontrolled environments. In such environments, gas source locations and the physical properties of the environment, such as humidity and temperature may be unknown or only sparse noisy local measurements are available. Example applications include air pollution monitoring, leakage detection, and search and rescue operations.This thesis addresses how to efficiently obtain and compute predictive models that accurately represent spatio-temporal gas distribution.Most statistical gas distribution modelling methods assume that gas dispersion can be modelled as a time-constant random process. While this assumption may hold in some situations, it is necessary to model variations over time in order to enable applications of gas distribution modelling for a wider range of realistic scenarios.This thesis proposes two time-dependent gas distribution modelling methods. In the first method, a temporal (sub-)sampling strategy is introduced. In the second method, a time-dependent gas distribution modelling approach is presented, which introduces a recency weight that relates measurement to prediction time. These contributions are presented and evaluated as an extension of a previously proposed method called Kernel DM+V using several simulation and real-world experiments. The results of comparing the proposed time-dependent gas distribution modelling approaches to the time-independent version Kernel DM+V indicate a consistent improvement in the prediction of unseen measurements, particularly in dynamic scenarios under the condition that there is a sufficient spatial coverage. Dynamic scenarios are often defined as environments where strong fluctuations and gas plume development are present.For mobile robot olfaction, we are interested in sampling strategies that provide accurate gas distribution models given a small number of samples in a limited time span. Correspondingly, this thesis addresses the problem of selecting the most informative locations to acquire the next samples.As a further contribution, this thesis proposes a novel adaptive sensor planning method. This method is based on a modified artificial potential field, which selects the next sampling location based on the currently predicted gas distribution and the spatial distribution of previously collected samples. In particular, three objectives are used that direct the sensor towards areas of (1) high predictive mean and (2) high predictive variance, while (3) maximising the coverage area. The relative weight of these objectives corresponds to a trade-off between exploration and exploitation in the sampling strategy. This thesis discusses the weights or importance factors and evaluates the performance of the proposed sampling strategy. The results of the simulation experiments indicate an improved quality of the gas distribution models when using the proposed sensor planning method compared to commonly used methods, such as random sampling and sampling along a predefined sweeping trajectory. In this thesis, we show that applying a locality constraint on the proposed sampling method decreases the travelling distance, which makes the proposed sensor planning approach suitable for real-world applications where limited resources and time are available. As a real-world use-case, we applied the proposed sensor planning approach on a micro-drone in outdoor experiments.Finally, this thesis discusses the potential of using gas distribution modelling and sensor planning in large-scale outdoor real-world applications. We integrated the proposed methods in a framework for decision-making in hazardous inncidents where gas leakage is involved and applied the gas distribution modelling in two real-world use-cases. Our investigation indicates that the proposed sensor planning and gas distribution modelling approaches can be used to inform experts both about the gas plume and the distribution of gas in order to improve the assessment of an incident.
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| 9. |
- Banaee, Hadi, 1986-
(författare)
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From Numerical Sensor Data to Semantic Representations : A Data-driven Approach for Generating Linguistic Descriptions
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In our daily lives, sensors recordings are becoming more and more ubiquitous. With the increased availability of data comes the increased need of systems that can represent the data in human interpretable concepts. In order to describe unknown observations in natural language, an artificial intelligence system must deal with several issues involving perception, concept formation, and linguistic description. These issues cover various subfields within artificial intelligence, such as machine learning, cognitive science, and natural language generation.The aim of this thesis is to address the problem of semantically modelling and describing numerical observations from sensor data. This thesis introduces data-driven approaches to perform the tasks of mining numerical data and creating semantic representations of the derived information in order to describe unseen but interesting observations in natural language.The research considers creating a semantic representation using the theory of conceptual spaces. In particular, the central contribution of this thesis is to present a data-driven approach that automatically constructs conceptual spaces from labelled numerical data sets. This constructed conceptual space then utilises semantic inference techniques to derive linguistic interpretations for novel unknown observations. Another contribution of this thesis is to explore an instantiation of the proposed approach in a real-world application. Specifically, this research investigates a case study where the proposed approach is used to describe unknown time series patterns that emerge from physiological sensor data. This instantiation first presents automatic data analysis methods to extract time series patterns and temporal rules from multiple channels of physiological sensor data, and then applies various linguistic description approaches (including the proposed semantic representation based on conceptual spaces) to generate human-readable natural language descriptions for such time series patterns and temporal rules.The main outcome of this thesis is the use of data-driven strategies that enable the system to reveal and explain aspects of sensor data which may otherwise be difficult to capture by knowledge-driven techniques alone. Briefly put, the thesis aims to automate the process whereby unknown observations of data can be 1) numerically analysed, 2) semantically represented, and eventually 3) linguistically described.
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| 10. |
- Bergsten, Pontus
(författare)
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Observers and controllers for Takagi-Sugeno fuzzy systems
- 2001
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis studies analysis and design issues for observers anc controllers for Takagi-Sugeno (TS) fuzzy systems. Many physical systems are nonlinear in nature and using the well known linear techniques for such systems may result in bad performance, and even instability. On the other hand, analysis and design of observers and controllers for general nonlinear systems tend to be a quite involved procedure. It turns out, however, that a TS fuzzy system is able to represent or approximate a large class of nonlinear systems. Developing methods for observation and control for TS systems should therefore be worthwile. The TS fuzzy systems considered in this thesis are allowed to have an affine term. This can be an advantage, because affine TS fuzzy systems may be able to approximate nonlinear functions to high accuracy with fewer rules than the TS fuzzy system with linear consequents only. It is shown that observer design is more difficult when the weights in the TS fuzzy systems depend on the estimated state, and an explicit design procedure is devised for that case. A reduced order observer is also proposed. To deal with modeling errors a fuzzy sliding mode approach is taken. The controller design is focused on affine TS fuzzy systems. Analysis and design of observer-based error state feedback controllers are proposed. Furthermore, it is also shown how recent results on classical gain scheduling may be used for control of affine TS fuzzy systems. Analysis and design for both observers and controllers are based on quadratic stability analysis, and in some cases, on robust quadratic stability analysis. Although this approach may be conservative, it often results in automatic design procedures based on optimization subject to linear matrix inequalities.
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