Paper Info
Title
Sensor-Based Probabilistic Roadmaps for Car-Like Robots
Abstract
This work deals with the sensor-based motion planning problem for car-like robots. Sensor-based versions of PRM and Lazy-PRM are used to exploit the information obtained from sensors and to compute a feasible collision-free path. The algorithm tries to reach the goal by executing the local method in the known free region. If it succeeds, a feasible path to the goal is found and the algorithm finishes. Otherwise, the algorithm executes more scans to extend its free space, and so on. Experimental results are promising.
Year
DOI
Venue
2004
10.1109/ENC.2004.1342618
ENC
Keywords
Field
DocType
mobile robots,path planning,sensors,Lazy-PRM,car-like robots,collision-free path,sensor-based motion planning problem,sensor-based probabilistic roadmap
Computer science,Probabilistic roadmaps,Real-time computing,Theoretical computer science,Artificial intelligence,Motion planning,Local method,Computer vision,Robot control,Exploit,Free space,Robot,Mobile robot
Conference
ISBN
Citations 
PageRank 
0-7695-2160-6
2
0.47
References 
Authors
14
2
Name
Order
Citations
PageRank
Abraham Sanchez1123.24
Rene Zapata2585.58