A new probabilistic roadmap method is presented for planning the path of a robotic sensor deployed in order to classify multiple fixed targets located in an obstacle-populated workspace. Existing roadmap methods have been successful at planning a robot path for the purpose of moving from an initial to a final configuration in a workspace by a minimum distance. But they are not directly applicab...

Autonomous motion planning addresses the problem of nding collision-free paths for moving objects robots among obstacles. In this report we consider robots operating in workspaces occupied by stationary, completely known obstacles. We describe a new approach to probabilistic roadmap planners (PRMs). The overall theme of the algorithm, called Lazy PRM, is to minimise the number of collision chec...

In today’s society, parallel computing is commonplace. Motion planning is a computationally complex problem in which solution methodologies can exploit parallelism for complex problems. In one approach to parallel sampling-based motion planning, the environment is divided among processors so that roadmaps can be constructed for each region of the environment independently. Afterwards, the roadm...