Combined Path and Motion Planning for Workspace Restricted Mobile Manipulators in Planetary Exploration
Gonzalo J. Paz-Delgado, J. Ricardo Sánchez-Ibáñez, Raúl Domínguez, Carlos J. Pérez-del-Pulgar, Frank Kirchner, Alfonso García-Cerezo
- 发表年份
- 2023
- 引用次数
- 7
- 访问权限
- 开放获取
摘要
A highly restricted workspace of the robotic arm may hinder to perform safely any autonomous mobile manipulation task with planetary exploration rovers. To ensure mission safety as well as high efficiency, a coupled path and motion planner for mobile manipulation is presented in this work. First, a Fast Marching Method based path planner generates a safe trajectory to reach the goal vicinity, avoiding obstacles and non-traversable areas in the scenario. The path planner is able to control the final rover orientation to ensure that the goal is finally reachable by the arm. Second, a 3D Fast Marching Method based motion planner generates the arm joints motion profile, by creating a 3D tunnel-like cost volume surrounding the already computed rover base trajectory. This tunnel makes use of an offline-computed safe workspace of the manipulator, thus ensuring that no self-collision will occur during the planned motion. The presented algorithm has been tested with multiple simulation experiments, benchmarked with an off-the-shelf motion planning library, and validated in a field test campaign with the rover <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SherpaTT</i> of DFKI Robotics Innovation Center. The tests consisted in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SherpaTT</i> approaching an interesting area on the scenario and performing a mobile manipulation sample scanning operation. These experiments have demonstrated that the proposed motion planner increases efficiency as well as ensures mission safety. This is thanks to, on the one hand, a coordinated base-arm movement that results in maximized efficiency in time terms, and, on the other hand, considering the manipulator workspace offline in the mobile manipulation motion planner to guarantee self-collision avoidance.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002