Real-time randomized path planning for robot navigation Export

@inproceedings{Bruce2002, abstract = {Mobile robots often must find a trajectory to another position in their environment, subject to constraints. This is the problem of planning a path through a continuous domain Rapidly-exploring random trees (RRTs) are a recently developed representation on which fast continuous domain path planners can be based. In this work, we build a path planning system based on RRTs that interleaves planning and execution, first evaluating it in simulation and then applying it to physical robots. Our planning algorithm, ERRT (execution extended RRT), introduces two novel extensions of previous RRT work, the waypoint cache and adaptive cost penalty search, which improve replanning efficiency and the quality of generated paths. ERRT is successfully applied to a real-time multi-robot system. Results demonstrate that ERRT is significantly more efficient for replanning than a basic RRT planner, performing competitively with or better than existing heuristic and reactive real-time path planning approaches. ERRT is a significant step forward with the potential for making path planning common on real robots, even in challenging continuous, highly dynamic domains.}, author = {Bruce, J. and Veloso, M.}, booktitle = {Intelligent Robots and System, 2002. IEEE/RSJ International Conference on}, citeulike-article-id = {3416651}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/IRDS.2002.1041624}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1041624}, doi = {10.1109/IRDS.2002.1041624}, journal = {Intelligent Robots and System, 2002. IEEE/RSJ International Conference on}, keywords = {crowd-control, robotics}, pages = {2383--2388 vol.3}, posted-at = {2008-10-16 09:01:40}, priority = {2}, title = {Real-time randomized path planning for robot navigation}, url = {http://dx.doi.org/10.1109/IRDS.2002.1041624}, volume = {3}, year = {2002} }

TY - CONF ID - Bruce2002 L3 - citeulike-article-id:3416651 N2 - Mobile robots often must find a trajectory to another position in their environment, subject to constraints. This is the problem of planning a path through a continuous domain Rapidly-exploring random trees (RRTs) are a recently developed representation on which fast continuous domain path planners can be based. In this work, we build a path planning system based on RRTs that interleaves planning and execution, first evaluating it in simulation and then applying it to physical robots. Our planning algorithm, ERRT (execution extended RRT), introduces two novel extensions of previous RRT work, the waypoint cache and adaptive cost penalty search, which improve replanning efficiency and the quality of generated paths. ERRT is successfully applied to a real-time multi-robot system. Results demonstrate that ERRT is significantly more efficient for replanning than a basic RRT planner, performing competitively with or better than existing heuristic and reactive real-time path planning approaches. ERRT is a significant step forward with the potential for making path planning common on real robots, even in challenging continuous, highly dynamic domains. JF - Intelligent Robots and System, 2002. IEEE/RSJ International Conference on EP - 2388 vol.3 TI - Real-time randomized path planning for robot navigation VL - 3 T2 - Intelligent Robots and System, 2002. IEEE/RSJ International Conference on SP - 2383 KW - crowd-control KW - robotics AU - Bruce, J AU - Veloso, M PY - 2002/// UR - http://dx.doi.org/10.1109/IRDS.2002.1041624 ER -