Interference detection among objects for operator assistance in virtual cooperative workspace

We propose an efficient method for detecting interference and potential collisions among objects to facilitate cooperative work in a virtual space. 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 causing interference and collisions. For this purpose specific pairs of faces belonging to any of the interfering objects found in the first stage are tested, and detailed computation is performed on a reduced amount of data. The experimental results show a better efficiency for the proposed method especially when there are complicated objects in the environment, in comparison with the conventional collision detection method