Dynamic Networks for Motion Planning in Multi-Robot Space Systems
Christopher M. Clark, Stephen M. Rock, Jean‐Claude Latombe
- 发表年份
- 2003
- 引用次数
- 44
- 访问权限
- 开放获取
摘要
A new motion planning framework is presented that enables multiple mobile robots with limited ranges of sensing and communication to maneuver and achieve goals safely in dynamic environments. The framework is applicable to both planetary rover and free-floating space robot applications. To combine the respective advantages of centralized and decentralized planning, this framework is based on the concept of centralized planning within dynamic robot networks. As the robots move in their environment, localized robot groups form networks, within which world models and robot goals can be shared. Whenever a new network gets formed, a fast centralized planner computes new coordinated trajectories on the fly, for all robots in the network. But planning over several robot networks is decentralized and distributed. The trajectory of each robot is re-computed whenever this robot contributes to forming a new network, as new information then becomes available to all robots in this network. Both simulated and real-robot experiments have validated the approach. The applicability of the framework to planetary rovers was demonstrated in both simulations and real robot experiments. Also, the framework's applicability to free-floating robots in a 3D space environment was demonstrated in simulation.
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