Kinetic Collision Detection: Algorithms and

Efficient Collision detection is important in many robotic tasks, from high-level motion planning in a static environment to low-level reactive behavior in dynamic situations. Especially challenging are problems in which multiple robots are moving among multiple moving obstacles. There is extensive work on the collision detection problem in robotics as well as in otherjelds. Many of the successful approaches exploit the continuity or coherence of the motion to reduce the collision checking overhead. In this paper; we present a number of collision detection algorithms formulated under the Kinetic Data Structures (KDS) framework, a framework,for designing and analyzing algorithms for objects in motion. The KDS frznzework leads to event-based algorithms that sample the state of different parts of the system only as often as necessary for the task at hand. Earlier work has demonstruted the theoretical eficiency of KDS algorithms. In this paper we present new algorithms and demonstrate their practical efficiency as well, by an implementation and direct comparison with classical broad and narrow phase collision detection techniques.