We explored approaches that offer full coverage path planning while simultaneously avoiding negative obstacles. These approaches are specific to unmanned ground vehicles (UGVs), which need to constantly interact with a traversable ground surface. We tested multiple potential solutions in simulation, and the results are presented herein. Full coverage path planner (FCPP) approaches were evaluated based on their ability to discretize their paths, use waypoints effectively, and be easily integrated with our current robot platform. For negative obstacles, we explored approaches that will integrate with our current navigation stack. The preferred solution will allow for teleoperation, waypoint navigation, and full autonomy while avoiding positive and negative obstacles.
Unmanned Ground Vehicle (UGV) Full Coverage Planning with Negative Obstacles
2023
45 pages
Report
Keine Angabe
Englisch
Computers, Control & Information Theory , Transportation , Artificial intelligence , Autonomous navigation , Autonomous systems , Autonomy , Change detection , Control systems , Detection , Detectors , Engineering , Engineers , Ground vehicles , Motion planning , Navigation , Robotics , Robots , Simulations , Unmanned ground vehicles
Multi-unmanned-surface-vehicle full-coverage path collaborative planning method
Europäisches Patentamt | 2020
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