Efficient collision detection among objects in arbitrary motion using multiple shape representations
We propose an efficient method for detecting potential collisions among multiple objects with arbitrary motion (translation and rotation) in 3D space. The method is useful for online monitoring and path planning in a 3D environment in which there are multiple independently-moving objects. The method consists of two main stages: 1) the coarse stage, an approximate test is performed to identify interfering objects in the entire workspace using octree representation of object shapes; and 2) the fine stage, polyhedral representation of object shapes is used to more accurately identify any object parts that might cause interference and collisions. For this purpose, specific pairs of faces belonging to any of the interfering objects found in the first stage are tested, thus performing detailed computation on a reduced amount of data. Experimental results, which demonstrate the efficiency of the proposed collision detection method, are given.