Multi-vehicle path planning in dynamically changing environments

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Lab Papers (GRASP)
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approximation theory
asymptotic stability
collision avoidance
computational geometry
concave programming
mobile robots
robot dynamics
asymptotic stability
collision free
mobile robot
multivehicle path planning
nonconvex feasibility optimization problem
nonholonomic multivehicle system
nonsmooth dynamical systems
obstacle avoidance
polygonal curve approximation
trajectory control
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Ahmadzadeh, Ali
Motee, Nader
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In this paper, we propose a path planning method for nonholonomic multi-vehicle system in presence of moving obstacles. The objective is to find multiple fixed length paths for multiple vehicles with the following properties: (i) bounded curvature (ii) obstacle avoidant (iii) collision free. Our approach is based on polygonal approximation of a continuous curve. Using this idea, we formulate an arbitrarily fine relaxation of the path planning problem as a nonconvex feasibility optimization problem. Then, we propound a nonsmooth dynamical systems approach to find feasible solutions of this optimization problem. It is shown that the trajectories of the nonsmooth dynamical system always converge to some equilibria that correspond to the set of feasible solutions of the relaxed problem. The proposed framework can handle more complex mission scenarios for multi-vehicle systems such as rendezvous and area coverage.

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2009-05-12
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Lab Papers (GRASP)
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2023-05-17T03:10:38.000
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Copyright 2009 IEEE. Reprinted from: Ahmadzadeh, A.; Motee, N.; Jadbabaie, A.; Pappas, G., "Multi-vehicle path planning in dynamically changing environments," Robotics and Automation, 2009. ICRA '09. IEEE International Conference on , vol., no., pp.2449-2454, 12-17 May 2009 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=5152520&isnumber=5152175 This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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