The Experts below are selected from a list of 14538 Experts worldwide ranked by ideXlab platform
Oussama Khatib - One of the best experts on this subject based on the ideXlab platform.
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elastic bands Connecting Path planning and control
International Conference on Robotics and Automation, 1993Co-Authors: Sean Quinlan, Oussama KhatibAbstract:Elastic bands are proposed as the basis for a framework to close the gap between global Path planning and real-time sensor-based robot control. An elastic band is a deformable collision-free Path. The initial shape of the elastic is the free Path generated by a planner. Subjected to artificial forces, the elastic band deforms in real time to a short and smooth Path that maintains clearance from the obstacles. The elastic continues to deform as changes in the environment are detected by sensors, enabling the robot to accommodate uncertainties and react to unexpected and moving obstacles. While providing a tight connection between the robot and its environment, the elastic band preserves the global nature of the planned Path. The framework is outlined, and an efficient implementation based on bubbles is discussed. >
Gokhan Inalhan - One of the best experts on this subject based on the ideXlab platform.
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Dynamically Feasible Probabilistic Motion Planning in Complex Environments for UAVs
'IntechOpen', 2021Co-Authors: Emre Koyuncu, Gokhan InalhanAbstract:Trajectory design of an air vehicle in dense and complex environments, while pushing the limits of the vehicle to full performance is a challenging problem in two facets. The first facet is the control system design over the full flight envelope and the second is the trajectory planning utilizing the full performance of the aircraft. In this work, we try to address the mostly second facet via the generating dynamically feasible trajectory planning. Hence, a real-time implementable two step planner strategy is implemented for obtaining 3D flight-Path generation for an Unmanned Aerial Vehicles in 3D Complex environments. Thus simplifications on the problem improved the real time implement ability. In our approach, initially, simplified version of the RRT planner is used for rapidly exploring the environment with an approximate line segments. The resulting Connecting Path is converted into flight way points through a line-of-sight segmentation. In second step, we explained two different methods to generate dynamically feasible trajectory. First one that we called Modal-Maneuver Based PRM Planner is developed for agile unmanned aerial vehicles that their maneuvers can be define with distinct modes. This allows significant decreases in control input space and thus search dimensions. In this approach the resulting connectivity Path and the corresponding milestones are refined with a single query Probabilistic Road Map (PRM) implementation that creates dynamically feasible flight Paths with distinct flight mode selections and their modal control inputs. In our second approach, remaining way points are connected with cubic (C2 continuous) B-Spline curve and this curve is repaired probabilistically to obtain a geometrically (prevents collisions) and dynamically feasible (considers velocity and acceleration constraints) Path. At the end, the time scaling approach allow dynamic achievability considering the velocity and acceleration limits of the aircrafts. Resulting strategy is tested on real-time physical hardware system using ITU CAL mobile robot testbed for 2D environments and simulations for 3D complex environments. Computational times showed satisfactory results to used for real time implementation for UAVs operations in challenging urban environments
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integration of Path maneuver planning in complex environments for agile maneuvering ucavs
Journal of Intelligent and Robotic Systems, 2010Co-Authors: Emre Koyuncu, Kemal N Ure, Gokhan InalhanAbstract:In this work, we consider the problem of generating agile maneuver profiles for Unmanned Combat Aerial Vehicles in 3D Complex environments. This problem is complicated by the fact that, generation of the dynamically and geometrically feasible flight trajectories for agile maneuver profiles requires search of nonlinear state space of the aircraft dynamics. This work suggests a two layer feasible trajectory/maneuver generation system. Integrated Path planning (considers geometrical, velocity and acceleration constraints) and maneuver generation (considers saturation envelope and attitude continuity constraints) system enables each layer to solve its own reduced order dimensional feasibility problem, thus simplifies the problem and improves the real time implement ability. In Trajectory Planning layer, to solve the time depended Path planning problem of an unmanned combat aerial vehicles, we suggest a two step planner. In the first step, the planner explores the environment through a randomized reachability tree search using an approximate line segment model. The resulting Connecting Path is converted into flight way points through a line-of-sight segmentation. In the second step, every consecutive way points are connected with B-Spline curves and these curves are repaired probabilistically to obtain a geometrically and dynamically feasible Path. This generated feasible Path is turned in to time depended trajectory with using time scale factor considering the velocity and acceleration limits of the aircraft. Maneuver planning layer is constructed upon multi modal control framework, where the flight trajectories are decomposed to sequences of maneuver modes and associated parameters. Maneuver generation algorithm, makes use of mode transition rules and agility metric graphs to derive feasible maneuver parameters for each mode and overall sequence. Resulting integrated system; tested on simulations for 3D complex environments, gives satisfactory results and promises successful real time implementation.
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a probabilistic b spline motion planning algorithm for unmanned helicopters flying in dense 3d environments
Intelligent Robots and Systems, 2008Co-Authors: Emre Koyuncu, Gokhan InalhanAbstract:This paper presents a strategy for improving motion planning of an unmanned helicopter flying in a dense and complex city-like environment. Although Sampling Based Motion planning algorithms have shown success in many robotic problems, problems that exhibit ldquonarrow passagerdquo properties involving kinodynamic planning of high dimensional vehicles like aerial vehicles still present computational challenges. In this work, to solve the kinodynamic motion planning problem of an unmanned helicopter, we suggest a two step planner. In the first step, the planner explores the environment through a randomized reachability tree search using an approximate line segment model. The resulting Connecting Path is converted into flight way points through a line-of-sight segmentation. In the second step, every consecutive way points are connected with B-Spline curves and these curves are repaired probabilistically to obtain a dynamically feasible Path. Numerical simulations in 3D indicate the ability of the method to provide real-time solutions in dense and complex environments.
Roland Siegwart - One of the best experts on this subject based on the ideXlab platform.
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structural inspection Path planning via iterative viewpoint resampling with application to aerial robotics
International Conference on Robotics and Automation, 2015Co-Authors: Andreas Bircher, Kostas Alexis, Michael Burri, Philipp Oettershagen, Sammy Omari, Thomas Mantel, Roland SiegwartAbstract:Within this paper, a new fast algorithm that provides efficient solutions to the problem of inspection Path planning for complex 3D structures is presented. The algorithm assumes a triangular mesh representation of the structure and employs an alternating two-step optimization paradigm to find good viewpoints that together provide full coverage and a Connecting Path that has low cost. In every iteration, the viewpoints are chosen such that the connection cost is reduced and, subsequently, the tour is optimized. Vehicle and sensor limitations are respected within both steps. Sample implementations are provided for rotorcraft and fixed-wing unmanned aerial systems. The resulting algorithm characteristics are evaluated using simulation studies as well as multiple real-world experimental test-cases with both vehicle types.
Sean Quinlan - One of the best experts on this subject based on the ideXlab platform.
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elastic bands Connecting Path planning and control
International Conference on Robotics and Automation, 1993Co-Authors: Sean Quinlan, Oussama KhatibAbstract:Elastic bands are proposed as the basis for a framework to close the gap between global Path planning and real-time sensor-based robot control. An elastic band is a deformable collision-free Path. The initial shape of the elastic is the free Path generated by a planner. Subjected to artificial forces, the elastic band deforms in real time to a short and smooth Path that maintains clearance from the obstacles. The elastic continues to deform as changes in the environment are detected by sensors, enabling the robot to accommodate uncertainties and react to unexpected and moving obstacles. While providing a tight connection between the robot and its environment, the elastic band preserves the global nature of the planned Path. The framework is outlined, and an efficient implementation based on bubbles is discussed. >
Emre Koyuncu - One of the best experts on this subject based on the ideXlab platform.
-
Dynamically Feasible Probabilistic Motion Planning in Complex Environments for UAVs
'IntechOpen', 2021Co-Authors: Emre Koyuncu, Gokhan InalhanAbstract:Trajectory design of an air vehicle in dense and complex environments, while pushing the limits of the vehicle to full performance is a challenging problem in two facets. The first facet is the control system design over the full flight envelope and the second is the trajectory planning utilizing the full performance of the aircraft. In this work, we try to address the mostly second facet via the generating dynamically feasible trajectory planning. Hence, a real-time implementable two step planner strategy is implemented for obtaining 3D flight-Path generation for an Unmanned Aerial Vehicles in 3D Complex environments. Thus simplifications on the problem improved the real time implement ability. In our approach, initially, simplified version of the RRT planner is used for rapidly exploring the environment with an approximate line segments. The resulting Connecting Path is converted into flight way points through a line-of-sight segmentation. In second step, we explained two different methods to generate dynamically feasible trajectory. First one that we called Modal-Maneuver Based PRM Planner is developed for agile unmanned aerial vehicles that their maneuvers can be define with distinct modes. This allows significant decreases in control input space and thus search dimensions. In this approach the resulting connectivity Path and the corresponding milestones are refined with a single query Probabilistic Road Map (PRM) implementation that creates dynamically feasible flight Paths with distinct flight mode selections and their modal control inputs. In our second approach, remaining way points are connected with cubic (C2 continuous) B-Spline curve and this curve is repaired probabilistically to obtain a geometrically (prevents collisions) and dynamically feasible (considers velocity and acceleration constraints) Path. At the end, the time scaling approach allow dynamic achievability considering the velocity and acceleration limits of the aircrafts. Resulting strategy is tested on real-time physical hardware system using ITU CAL mobile robot testbed for 2D environments and simulations for 3D complex environments. Computational times showed satisfactory results to used for real time implementation for UAVs operations in challenging urban environments
-
integration of Path maneuver planning in complex environments for agile maneuvering ucavs
Journal of Intelligent and Robotic Systems, 2010Co-Authors: Emre Koyuncu, Kemal N Ure, Gokhan InalhanAbstract:In this work, we consider the problem of generating agile maneuver profiles for Unmanned Combat Aerial Vehicles in 3D Complex environments. This problem is complicated by the fact that, generation of the dynamically and geometrically feasible flight trajectories for agile maneuver profiles requires search of nonlinear state space of the aircraft dynamics. This work suggests a two layer feasible trajectory/maneuver generation system. Integrated Path planning (considers geometrical, velocity and acceleration constraints) and maneuver generation (considers saturation envelope and attitude continuity constraints) system enables each layer to solve its own reduced order dimensional feasibility problem, thus simplifies the problem and improves the real time implement ability. In Trajectory Planning layer, to solve the time depended Path planning problem of an unmanned combat aerial vehicles, we suggest a two step planner. In the first step, the planner explores the environment through a randomized reachability tree search using an approximate line segment model. The resulting Connecting Path is converted into flight way points through a line-of-sight segmentation. In the second step, every consecutive way points are connected with B-Spline curves and these curves are repaired probabilistically to obtain a geometrically and dynamically feasible Path. This generated feasible Path is turned in to time depended trajectory with using time scale factor considering the velocity and acceleration limits of the aircraft. Maneuver planning layer is constructed upon multi modal control framework, where the flight trajectories are decomposed to sequences of maneuver modes and associated parameters. Maneuver generation algorithm, makes use of mode transition rules and agility metric graphs to derive feasible maneuver parameters for each mode and overall sequence. Resulting integrated system; tested on simulations for 3D complex environments, gives satisfactory results and promises successful real time implementation.
-
a probabilistic b spline motion planning algorithm for unmanned helicopters flying in dense 3d environments
Intelligent Robots and Systems, 2008Co-Authors: Emre Koyuncu, Gokhan InalhanAbstract:This paper presents a strategy for improving motion planning of an unmanned helicopter flying in a dense and complex city-like environment. Although Sampling Based Motion planning algorithms have shown success in many robotic problems, problems that exhibit ldquonarrow passagerdquo properties involving kinodynamic planning of high dimensional vehicles like aerial vehicles still present computational challenges. In this work, to solve the kinodynamic motion planning problem of an unmanned helicopter, we suggest a two step planner. In the first step, the planner explores the environment through a randomized reachability tree search using an approximate line segment model. The resulting Connecting Path is converted into flight way points through a line-of-sight segmentation. In the second step, every consecutive way points are connected with B-Spline curves and these curves are repaired probabilistically to obtain a dynamically feasible Path. Numerical simulations in 3D indicate the ability of the method to provide real-time solutions in dense and complex environments.