Probabilistic Roadmaps: A Motion Planning Approach Based on Active Learning
Jean‐Claude Latombe · 2006
Motion planning is the ability that an autonomous robot must possess to compute its motions, in order to perform tasks such as navigating from one location to another, assembling a product, fetching an object, building a map of an environment, inspecting a structure, tracking an un-predictable target, or climbing a cliff. A new motion-planning approach - Probabilistic RoadMap (PRM) planning - has emerged, which takes advantage of such techniques. The talk will discuss how a better understanding of these properties is already making it possible to design faster PRM planners capable of solving increasingly more complex problems