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A simple and efficient randomized algorithm is presented for solving single-query path planning problems in high-dimensional configuration spaces. The method works by incrementally building two Rapidly-exploring Random Trees (RRTs) rooted at the start and the goal configurations. The trees each explore space around them and also advance towards each other(More)
This paper addresses the problem of planning the motion of one or more pursuers in a polygonal environment to eventually \see" an evader that is unpredictable, has unknown initial position, and is capable of moving arbitrarily fast. This problem was rst introduced by Suzuki and Yamashita. Our study of this problem is motivated in part by robotics(More)
Sampling-based planners have solved difficult problems in many applications of motion planning in recent years. In particular, techniques based on the Rapidly-exploring Random Trees (RRTs) have generated highly successful single-query planners. Even though RRTs work well on many problems, they have weaknesses which cause them to explore slowly when the(More)
This paper addresses the problem of planning the motion of one or more pursuers in a polygonal environment to eventually \see" an evader that is unpredictable, has unknown initial position, and is capable of moving arbitrarily fast. A visibility region is associated w i t h e ach pursuer, and the goal is to guarantee that the evader will ultimately lie in(More)
Sampling based planners have become increasingly efficient in solving the problems of classical motion planning and its applications. In particular, techniques based on the rapidly-exploring random trees (RRTs) have generated highly successful single-query planners. Recently, a variant of this planner called dynamic-domain RRT was introduced by Yershova et(More)