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Online motion planning for autonomous vehicles in vast environments
Boekbijdrage - Boekhoofdstuk Conferentiebijdrage
© 2018 IEEE. Nowadays, the potential of autonomous vehicles for order picking and material transport in vast environments with large amounts of obstacles is only exploited to a limited extent. In order to realize free, time-optimal motion of autonomous vehicles through such complex environments, this paper presents a novel motion planning approach. The approach combines a global path planner with a local trajectory generator. The global planner finds a path through the complete environment, taking only the stationary obstacles into account. The local trajectory generator computes a detailed trajectory in a local frame around the global path, accounting for both stationary and moving obstacles. This trajectory is parameterized as a spline, and is obtained by solving an optimal control problem. In order to always include the latest information about the environment, the optimal control problem is solved online with a receding horizon. The paper demonstrates the potential of the proposed method with extensive numerical simulations. In addition, it presents an experimental validation in which a KUKA youBot moves through an obstructed environment. To facilitate the numerical and experimental validation of the presented method, it is embodied in a user-friendly open-source software toolbox.
Boek: 2018 IEEE 15TH INTERNATIONAL WORKSHOP ON ADVANCED MOTION CONTROL (AMC)
Pagina's: 114 - 119
Jaar van publicatie:2018
Authors from:Government, Higher Education