| 1. |
- Patel, Chirag, et al.
(författare)
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DBGC : Dimension-Based Generic Convolution Block for Object Recognition
- 2022
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 22:5
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Tidskriftsartikel (refereegranskat)abstract
- The object recognition concept is being widely used a result of increasing CCTV surveillance and the need for automatic object or activity detection from images or video. Increases in the use of various sensor networks have also raised the need of lightweight process frameworks. Much research has been carried out in this area, but the research scope is colossal as it deals with open-ended problems such as being able to achieve high accuracy in little time using lightweight process frameworks. Convolution Neural Networks and their variants are widely used in various computer vision activities, but most of the architectures of CNN are application-specific. There is always a need for generic architectures with better performance. This paper introduces the Dimension-Based Generic Convolution Block (DBGC), which can be used with any CNN to make the architecture generic and provide a dimension-wise selection of various height, width, and depth kernels. This single unit which uses the separable convolution concept provides multiple combinations using various dimension-based kernels. This single unit can be used for height-based, width-based, or depth-based dimensions; the same unit can even be used for height and width, width and depth, and depth and height dimensions. It can also be used for combinations involving all three dimensions of height, width, and depth. The main novelty of DBGC lies in the dimension selector block included in the proposed architecture. Proposed unoptimized kernel dimensions reduce FLOPs by around one third and also reduce the accuracy by around one half; semi-optimized kernel dimensions yield almost the same or higher accuracy with half the FLOPs of the original architecture, while optimized kernel dimensions provide 5 to 6% higher accuracy with around a 10 M reduction in FLOPs.
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| 2. |
- Drezner, Jonathan A, et al.
(författare)
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Abnormal electrocardiographic findings in athletes : recognising changes suggestive of cardiomyopathy.
- 2013
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Ingår i: British Journal of Sports Medicine. - : BMJ. - 0306-3674 .- 1473-0480. ; 47:3, s. 137-52
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Tidskriftsartikel (refereegranskat)abstract
- Cardiomyopathies are a heterogeneous group of heart muscle diseases and collectively are the leading cause of sudden cardiac death (SCD) in young athletes. The 12-lead ECG is utilised as both a screening and diagnostic tool for detecting conditions associated with SCD. Fundamental to the appropriate evaluation of athletes undergoing ECG is an understanding of the ECG findings that may indicate the presence of an underlying pathological cardiac disorder. This article describes ECG findings present in cardiomyopathies afflicting young athletes and outlines appropriate steps for further evaluation of these ECG abnormalities. The ECG findings defined as abnormal in athletes were established by an international consensus panel of experts in sports cardiology and sports medicine.
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| 3. |
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| 4. |
- Mukundan, Arvind, et al.
(författare)
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Kalam Rover
- 2021
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Ingår i: AIAA SCITECH 2022 Forum, January 3-7 2022, San Diego, CA & Virtual. - Reston, Virginia : American Institute of Aeronautics and Astronautics Inc, AIAA.
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Konferensbidrag (refereegranskat)abstract
- Our knowledge about the formation and feasibility for the near-future manned mission of the lunar farside highlands is still restricted since relatively few missions and research studies have been conducted. However, there are many interesting particulars on the far side, and finding sufficient evidence for practically accessible water ice near those land sites can potentially increase the prospect for future human colonization. Therefore, this paper proposes a novel rover design that would provide a base foundation for future human missions and lunar outposts. A small, lightweight, and low-power consuming rover have been developed, designed, and analyzed to perform in-situ research and excavation on the lunar far side. This paper put forward the scientific objectives, the payloads on the rover, the design of the rover with integrated excavation drill mechanism, the telemetry & telecommand, the technology, and the power and mass budget of building such a lunar rover.
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| 5. |
- Mukundan, Arvind, et al.
(författare)
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The Dvaraka Initiative: Mars's First Permanent Human Settlement Capable of Self-Sustenance
- 2023
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Ingår i: Aerospace. - : MDPI. - 2226-4310. ; 10:3
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Tidskriftsartikel (refereegranskat)abstract
- From the farthest reaches of the universe to our own galaxy, there are many different celestial bodies that, even though they are very different, each have their own way of being beautiful. Earth, the planet with the best location, has been home to people for as long as we can remember. Even though we cannot be more thankful for all that Earth has given us, the human population needs to grow so that Earth is not the only place where people can live. Mars, which is right next to Earth, is the answer to this problem. Mars is the closest planet and might be able to support human life because it is close to Earth and shares many things in common. This paper will talk about how the first settlement on Mars could be planned and consider a 1000-person colony and the best place to settle on Mars, and make suggestions for the settlement's technical, architectural, social, and economic layout. By putting together assumptions, research, and estimates, the first settlement project proposed in this paper will suggest the best way to colonize, explore, and live on Mars, which is our sister planet.
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| 6. |
- Patel, Akash, et al.
(författare)
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Control of ARWs
- 2023
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Ingår i: Aerial Robotic Workers. - : Elsevier. - 9780128149096 ; , s. 49-65
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This Chapter focuses on Aerial Robotic Workers (ARWs) various control methods to successfully track the desired states, waypoints, and trajectories. Additionally, this Chapter discusses the regulation from the motor commands level to the accurate tracking of waypoints in 3D space. Various model-based control frameworks are presented based on the modeled dynamics of the Modeling for ARWs (Chapter 3). Initially, a classical Proportional-Integral-Derivative (PID) control scheme is introduced, while in the sequel, a Linear Quadratic Regulator (LQR) and a Model Predictive Controller (MPC) are designed for the linearized dynamics of ARWs. In the sequel, a Nonlinear-MPC (NMPC) version of the simplified position control scheme is given. Finally, a switching MPC is presented for the attitude regulation of a reconfigurable ARW.
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| 7. |
- Patel, Akash, et al.
(författare)
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Design and Model Predictive Control of a Mars Coaxial Quadrotor
- 2022
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Ingår i: 2022 IEEE Aerospace Conference (AERO). - : IEEE.
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Konferensbidrag (refereegranskat)abstract
- Mars has been a prime candidate for planetary explo-ration of the solar system because of the science discoveries that support chances of future habitation on this planet. The Mars exploration landers and rovers have laid the foundation of our understanding of the planet's atmosphere and terrain. However, the rovers have presented limitations in terms of their pace, travers ability, and exploration capabilities from the ground and thus, one of the main field of interest for future robotic mission to Mars is to enhance the autonomy of this exploration vehicles. Martian caves and lava tubes like terrains, which consists of uneven ground, poor visibility and confined space, makes it impossible for wheel based rovers to navigate through these areas. In order to address these limitations and advance the exploration capability in a Martian terrain, this article presents the design and control of a novel coaxial quadrotor Micro Aerial Vehicle (MAV). As it will be presented, the key contributions on the design and control architecture of the proposed Mars coaxial quadrotor, are introducing an alternative and more enhanced, from a control point of view concept, when compared in terms of autonomy to Ingenuity. Based on the presented design, the article will introduce the mathematical modelling and automatic control framework of the vehicle that will consist of a linearised model of a co-axial quadrotor and a corresponding Model Pre-dictive Controller (MPC) for the trajectory tracking. Among the many models, proposed for the aerial flight on Mars, a reliable control architecture lacks in the related state of the art. The MPC based closed loop responses of the proposed MAV will be verified in different conditions during the flight with additional disturbances, induced to replicate a real flight scenario. For the model validation purpose, the Mars coaxial quadrotor is sim-ulated inside a Martian environment with related atmospheric conditions in the Gazebo simulator, which will use the proposed MPC controller for following an a priory defined trajectory. In order to further validate the proposed control architecture and prove the efficacy of the suggested design, the introduced Mars coaxial quadrotor and the MPC scheme will be compared to a PID-type controller, similar to the Ingenuity helicopter's control architecture for the position and the heading.
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| 8. |
- Patel, Akash, et al.
(författare)
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Exploration with ARWs
- 2023
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Ingår i: Aerial Robotic Workers: Design, Modeling, Control, Vision, and Their Applications. - : Elsevier. - 9780128149096 ; , s. 109-127
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter presents an overview of various exploration schemes with single and multi Aerial Robotic Workers (ARWs) and their applications in Search and Rescue, Environmental Monitoring, and planetary exploration missions, under the assumption that the map is partially known or completely unknown. The presented methods in the chapter are in line with the field deployment of the ARWs in subterranean and planetary exploration missions. The addressed questions will include the operating environment configuration and path planning methods for single and multi-robot exploration. The chapter will also briefly present two exploration strategies in terms of frontier and sampling-based exploration algorithms. More specifically, frontier-based and Rapidly Exploring Random Tree (RRT)-based exploration methodologies with results will be explained in detail.
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| 9. |
- Patel, Akash, et al.
(författare)
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Fast Planner for MAV Navigation in Unknown Environments Based on Adaptive Search of Safe Look-Ahead Poses
- 2022
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Ingår i: 2022 30th Mediterranean Conference on Control and Automation (MED). - : IEEE. ; , s. 545-550
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Konferensbidrag (refereegranskat)abstract
- Autonomous navigation capability is a crucial part for deploying robots in an unknown environment. In this article a reactive local planner for autonomous and safe navigation in subterranean environment is presented. The proposed planning framework navigates the MAV forward in a tunnel such that the MAV gains more information about the environment while avoiding obstacles. The proposed planning architecture works solely based on the information of local surrounding of the MAV thus, making navigation simple yet fast. One of the biggest novelties of the article comes from solving the combined problem of autonomous navigation and obstacle avoidance. The proposed algorithm for selecting the next way point of interest also accounts in the safety margin for traversing to such way point. The approach presented in this article is also different from classical map based global planning algorithms because it favours the next way point away from obstacles in way point selection process and thus providing a safe path for incremental forward navigation. The approach is validated by simulating a MAV equipped with the proposed reactive local planner in order for the MAV to navigate in a subterranean cave environment.
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| 10. |
- Patel, Akash, et al.
(författare)
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Modeling for ARWs
- 2023
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Ingår i: Aerial Robotic Workers. - : Elsevier. - 9780128149096 ; , s. 31-47
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This Chapter presents an overview of the aerial vehicles' rigid body dynamics. First, the Euler equations, Direction Cosine Matrix (DCM), and Quaternion formulations that describe the attitude of an ARW are presented, while in the sequel, the full nonlinear model based on the Newton-Euler equations is presented along with a simplified nonlinear position model. Finally, the modeling of a reconfigurable ARW is presented.
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| 11. |
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| 12. |
- Patel, Akash, et al.
(författare)
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REF: A Rapid Exploration Framework for Deploying Autonomous MAVs in Unknown Environments
- 2023
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Ingår i: Journal of Intelligent and Robotic Systems. - : Springer. - 0921-0296 .- 1573-0409. ; 108
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Tidskriftsartikel (refereegranskat)abstract
- Exploration and mapping of unknown environments is a fundamental task in applications for autonomous robots. In this article, we present a complete framework for deploying Micro Aerial Vehicles (MAVs) in autonomous exploration missions in unknown subterranean areas. The main motive of exploration algorithms is to depict the next best frontier for the MAV such that new ground can be covered in a fast, safe yet efficient manner. The proposed framework uses a novel frontier selection method that also contributes to the safe navigation of autonomous MAVs in obstructed areas such as subterranean caves, mines, and urban areas. The framework presented in this work bifurcates the exploration problem in local and global exploration. The proposed exploration framework is also adaptable according to computational resources available onboard the MAV which means the trade-off between the speed of exploration and the quality of the map can be made. Such capability allows the proposed framework to be deployed in subterranean exploration and mapping as well as in fast search and rescue scenarios. The performance of the proposed framework is evaluated in detailed simulation studies with comparisons made against a high-level exploration-planning framework developed for the DARPA Sub-T challenge as it will be presented in this article.
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| 13. |
- Patel, Akash
(författare)
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Towards Enabling Exploration of Planetary Subterranean Environments using Unmanned Aerial Vehicles
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis presents a novel navigation framework established to enable the exploration of planetary subterranean areas with Unmanned Aerial Vehicles (UAVs). The key contributions of this thesis work form a robot-safe rapid navigation framework that utilizes a novel bifurcating frontier-based exploration approach. UAVs (limited to quadrotors in this work) have superior navigation capabilities compared to ground robots in terms of 3D navigation as well as fast and versatile Traversability. Utilizing this advantage, this thesis investigates exploration and path-planning problems and presents novel mission behavior-oriented exploration strategies that are evaluated through either simulation with true physics and atmospheric models of planetary bodies or real-world deployment in subterranean areas. The work included in this thesis is focused on two main research directions. The first direction establishes a novel coaxial quadrotor design that can operate in the thin atmosphere of Mars and utilize the Mars Coaxial Quadrotor (MCQ) to develop an energy-efficient exploration algorithm that leads to autonomously map Martian underground lava channel through true atmospheric model-based simulations. While the second direction establishes a Rapid Exploration Framework (REF) for the real-world deployment for the exploration of GPS-denied underground environments with UAVs. The contributions in the two directions are merged to develop a field-hardened autonomous exploration pipeline for UAVs that focuses on maintaining the heading vector of the UAV towards the most unknown area ahead of the UAV. While also bifurcating the exploration problem in local and global exploration for rapid navigation towards the unknown areas in the field of view and quickly globally re-positioning to a partially explored area. For navigating to the exploration goal of the UAV, it utilizes an expendable grid-based risk-aware path planning framework (D$^{*}_{+}$) that explicitly models unknown areas as risk and plans paths in safe space and for local obstacle avoidance and control the framework utilizes Artificial Potential Fields (APF) and a nonlinear Model Predictive Control based reference tracking scheme.Based on the learnings from field experiments and limitations of state-of-the-art grid-based planning methods on large-scale maps, the final contribution of the thesis establishes a Grid + Graph oriented Traversability-aware exploration and planning framework. The graph-based exploration method proposed in this thesis utilizes geometric shapes to define local traversable paths for the UAV to navigate to the local exploration goal. While utilizing a traversable graph that incrementally plans paths to the edge vertex of sub-maps in the direction of the global re-position goal. The strategy is evaluated extensively in simulations in subterranean urban, tunnel, and cave environments while it is also tested in real-world deployment at test mines of EPIROC and LKAB in Sweden.
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| 14. |
- Patel, Akash, et al.
(författare)
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Towards energy efficient autonomous exploration of Mars lava tube with a Martian coaxial quadrotor
- 2023
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Ingår i: Advances in Space Research. - : Elsevier. - 0273-1177 .- 1879-1948. ; 71:9, s. 3837-3854
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Tidskriftsartikel (refereegranskat)abstract
- Mapping and exploration of a Martian terrain with an aerial vehicle has become an emerging research direction, since the successful flight demonstration of the Mars helicopter Ingenuity. Although the autonomy and navigation capability of the state of the art Mars helicopter has proven to be efficient in an open environment, the next area of interest for exploration on Mars are caves or ancient lava tube like environments, especially towards the never-ending search of life on other planets. This article presents an autonomous exploration mission based on a modified frontier approach along with a risk aware planning and integrated collision avoidance scheme with a special focus on energy aspects of a custom designed Mars Coaxial Quadrotor (MCQ) in a Martian simulated lava tube. One of the biggest novelties of the article stems from addressing the exploration capability, while rapidly exploring in local areas and intelligently global re-positioning of the MCQ when reaching dead ends in order to efficiently use the battery based consumed energy, while increasing the volume of the exploration. The proposed novel algorithm for the Martian exploration is able to select the next way point of interest, such that the MCQ keeps its heading towards the local exploration direction where it will find maximum information about the surroundings. The proposed three layer cost based global re-position point selection assists in rapidly redirecting the MCQ to previously partially seen areas that could lead to more unexplored part of the lava tube. The Martian fully simulated mission presented in this article takes into consideration the fidelity of physics of Mars condition in terms of thin atmosphere, low surface pressure and low gravity of the planet, while proves the efficiency of the proposed scheme in exploring an area that is particularly challenging due to the subterranean-like environment. The proposed exploration-planning framework is also validated in simulation by comparing it against the graph based exploration planner. Intensive simulations with true Mars conditions are carried out in order to validate and benchmark our approach in a utmost realistic Mars lava tube exploration scenario using a Mars Coaxial Quadrotor.
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| 15. |
- Patel, Akash, et al.
(författare)
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Towards field deployment of MAVs in adaptive exploration of GPS-denied subterranean environments
- 2024
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Ingår i: Robotics and Autonomous Systems. - : Elsevier. - 0921-8890 .- 1872-793X. ; 176
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Tidskriftsartikel (refereegranskat)abstract
- Exploration and safe navigation in previously unknown GPS-denied obstructed areas are major challenges for autonomous robots when deployed in subterranean environments. In response, this work establishes an Exploration-Planning framework developed for the real-world deployment of Micro Aerial Vehicles (MAVs) in subterranean exploration missions. The fundamental task for an autonomous MAV to navigate in an unknown area, is to decide where to look while navigating such that the MAV will acquire more information about the surrounding. The work presented in this article focuses around 3D exploration of large-scale caves or multi-branched tunnel like structures, while still prioritizing the Look-Ahead and Move-Forward approach for fast navigation in previously unknown areas. In order to achieve such exploration behaviour, the proposed work utilizes a two-layer navigation approach. The first layer deals with computing traversable frontiers to generate the look ahead poses in the constrained field of view, aligned with the MAV’s heading vector that leads to rapid continuous exploration. The proposed frontier distribution based switching goal selection approach allows the MAV to explore various terrains, while still regulating the MAV’s heading vector. The second layer of the proposed scheme deals with global cost based navigation of the MAV to the potential junction in a multi-branched tunnel system leading to a continuous exploration of partially seen areas. The proposed framework is a combination of a novel frontier goal selection approach, risk-aware expandable grid based path planning, nonlinear model predictive control and artificial potential fields based on local reactive navigation, obstacle avoidance, and control for the autonomous deployment of MAVs in extreme environments.
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| 16. |
- Patel, Akash, et al.
(författare)
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Traversability Aware graph-based Subterranean Exploration with Unmanned Aerial Vehicles
- 2023
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Ingår i: 22nd IFAC World Congress: Proceedings. - : Elsevier. ; , s. 9263-9268
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Konferensbidrag (refereegranskat)abstract
- Subterranean exploration and mapping for search and rescue robotics have become an emerging research direction since the DARPA organized Subterranean Challenge. As part of development efforts within the team CoSTAR (Collaborative SubTerranean Autonomous Robots) in the Sub-T challenge, this work establishes a novel traversable graph-based exploration strategy that utilizes frontiers for local navigation and a fast collision risk-aware graph building for global navigation. The exploration strategy extracts frontiers in an unknown area that contribute to safe navigation while maximizing information gain for the robot. The exploration problem is further bifurcated into local and global exploration for faster decision-making at junctions with the goal of rapidly exploring the area. The local exploration guarantees collision-free straight-line paths to informative frontiers for rapid forward navigation, while global re-positioning utilizes a traversable graph subject to geometrical collision checks within the occupancy map. The pathfinding in a graph is addressed using a heuristic, which combines risk margins and travel costs to assist in short yet safe paths to the global frontier in case of a dead end in local exploration. The presented exploration strategy is developed with the goal of making exploration algorithms platform agnostic in order to be able to use it with aerial, as well as ground robots. The proposed method is also evaluated against different state-of-the-art exploration planners in simulated fixed-time budget-based exploration missions on an Unmanned Aerial Vehicle (UAV) in order to benchmark the capabilities and highlight the novelty.
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| 17. |
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| 18. |
- Saucedo, Mario Alberto Valdes, et al.
(författare)
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Belief Scene Graphs: Expanding Partial Scenes with Objects through Computation of Expectation
- 2024
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Konferensbidrag (refereegranskat)abstract
- In this article, we propose the novel concept of Belief Scene Graphs, which are utility-driven extensions of partial 3D scene graphs, that enable efficient high-level task planning with partial information. We propose a graph-based learning methodology for the computation of belief (also referred to as expectation) on any given 3D scene graph, which is then used to strategically add new nodes (referred to as blind nodes) that are relevant to a robotic mission. We propose the method of Computation of Expectation based on Correlation Information (CECI), to reasonably approximate real Belief/Expectation, by learning histograms from available training data. A novel Graph Convolutional Neural Network (GCN) model is developed, to learn CECI from a repository of 3D scene graphs. As no database of 3D scene graphs exists for the training of the novel CECI model, we present a novel methodology for generating a 3D scene graph dataset based on semantically annotated real-life 3D spaces. The generated dataset is then utilized to train the proposed CECI model and for extensive validation of the proposed method. We establish the novel concept of \textit{Belief Scene Graphs} (BSG), as a core component to integrate expectations into abstract representations. This new concept is an evolution of the classical 3D scene graph concept and aims to enable high-level reasoning for task planning and optimization of a variety of robotics missions. The efficacy of the overall framework has been evaluated in an object search scenario, and has also been tested in a real-life experiment to emulate human common sense of unseen-objects. For a video of the article, showcasing the experimental demonstration, please refer to the following link: \url{https://youtu.be/hsGlSCa12iY}
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| 19. |
- Saucedo, Mario A. V., et al.
(författare)
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EAT: Environment Agnostic Traversability for reactive navigation
- 2024
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Ingår i: Expert systems with applications. - : Elsevier Ltd. - 0957-4174 .- 1873-6793. ; 244
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Tidskriftsartikel (refereegranskat)abstract
- This work presents EAT (Environment Agnostic Traversability for Reactive Navigation) a novel framework for traversability estimation in indoor, outdoor, subterranean (SubT) and other unstructured environments. The architecture provides updates on traversable regions online during the mission, adapts to varying environments, while being robust to noisy semantic image segmentation. The proposed framework considers terrain prioritization based on a novel decay exponential function to fuse the semantic information and geometric features extracted from RGB-D images to obtain the traversability of the scene. Moreover, EAT introduces an obstacle inflation mechanism on the traversability image, based on mean-window weighting module, allowing to adapt the proximity to untraversable regions. The overall architecture uses two LRASPP MobileNet V3 large Convolutional Neural Networks (CNN) for semantic segmentation over RGB images, where the first one classifies the terrain types and the second one classifies see-through obstacles in the scene. Additionally, the geometric features profile the underlying surface properties of the local scene, extracting normals from depth images. The proposed scheme was integrated with a control architecture in reactive navigation scenarios and was experimentally validated in indoor and outdoor environments as well as in subterranean environments with a Pioneer 3AT mobile robot.
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| 20. |
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| 21. |
- V. Saucedo, Mario A., et al.
(författare)
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Event Camera and LiDAR based Human Tracking for Adverse Lighting Conditions in Subterranean Environments
- 2023
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Ingår i: 22nd IFAC World Congress. - : Elsevier. ; , s. 9257-9262
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Konferensbidrag (refereegranskat)abstract
- In this article, we propose a novel LiDAR and event camera fusion modality for subterranean (SubT) environments for fast and precise object and human detection in a wide variety of adverse lighting conditions, such as low or no light, high-contrast zones and in the presence of blinding light sources. In the proposed approach, information from the event camera and LiDAR are fused to localize a human or an object-of-interest in a robot's local frame. The local detection is then transformed into the inertial frame and used to set references for a Nonlinear Model Predictive Controller (NMPC) for reactive tracking of humans or objects in SubT environments. The proposed novel fusion uses intensity filtering and K-means clustering on the LiDAR point cloud and frequency filtering and connectivity clustering on the events induced in an event camera by the returning LiDAR beams. The centroids of the clusters in the event camera and LiDAR streams are then paired to localize reflective markers present on safety vests and signs in SubT environments. The efficacy of the proposed scheme has been experimentally validated in a real SubT environment (a mine) with a Pioneer 3AT mobile robot. The experimental results show real-time performance for human detection and the NMPC-based controller allows for reactive tracking of a human or object of interest, even in complete darkness.
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