We present new realtime path planning and collision avoidance algorithms for an autonomous rover equipped with a laser range finder to be used as a platform for multi-agent navigation and control in unknown environments. For successful navigation, such tasks as localization, map-building, and collision avoidance should be handled at the vehicle level. The proposed architecture covers these aspects of robotic path- planning in a modular and robust manner, allowing quicker development of more sophisticated path-planners. Using a conventional SLAM algorithm, a feature map and the location of the vehicle is obtained. The information for orientation and distance of the obstacles ahead is available from a laser range finder. The proposed collision avoidance algorithm provides multiple paths to guide the vehicle through the environment. The system acts as a self-contained extendable platform for development and testing of high-level pathfinders.
SLAM (robots),collision avoidance,laser ranging,message passing,mobile robots,multi-robot systems,robot vision,SLAM algorithm,autonomous rover,car like online navigation testbed,collision avoidance algorithms,feature map,laser range finder,message passing architecture,multiagent navigation,path planning algorithms,unknown environments,vehicle location
Computer science,Computer network,Testbed,Real-time computing,Artificial intelligence,Simultaneous localization and mapping,Message passing,Motion planning,Computer vision,Feature extraction,Collision,Modular design,Mobile robot