Lazy PRM algorithm Remove node/Edge it goal For Nodes. remove all Build roadmap For Edges, just remove the edge Shortest Path(A") Enhancement Remove Colliding node/edge No path found Collision Check nodes Collision Check ed Lazy prm algorithm Node enhancement qinit qgoal Add 2 uniforml Build Roadmap Add 2 clustered around midpoints of removed eages Shortest Node Path(a") Enhancement Remove Colliding node/edge No path found Collision Check nodes Check edges Collisio
Lazy PRM Algorithm Remove Node/Edge For Nodes, remove all edges For Edges, just remove the edge Build Roadmap Shortest Path (A*) Check Nodes Check Edges Remove Colliding node/edge Node Enhancement Collision Collision No path found qinit, qgoal Lazy PRM Algorithm Node Enhancement Add ½ uniformly Add ½ clustered around midpoints of removed edges Build Roadmap Shortest Path (A*) Check Nodes Check Edges Remove Colliding node/edge Node Enhancement Collision Collision No path found qinit, qgoal
Where Prms fall short Using PrM 1. Construct roadmap 2. A finds path 3. Must derive control inputs from path Path itself is not enough need control inputs Cannot always execute an arbitrary path Path Planning in the real World Real World robots s Have inertia Have limited controlability a Have limited sensors face a dynamic environment Face an unreliable environment Static planners(ex PRM)are not sufficient
Where PRMs Fall Short Using PRM 1. Construct roadmap 2. A* finds path in roadmap 3. Must derive control inputs from path Path itself is not enough: need control inputs Cannot always execute an arbitrary path Path Planning in the Real World Real World Robots Have inertia Have limited controlability Have limited sensors Face a dynamic environment Face an unreliable environment Static planners (ex. PRM) are not sufficient Have limited sensors