Robotic manipulator real-time collision avoidance is a safety critical mode of teleoperation where motion commands which would result in a collision are disallowed. To achieve real-time performance, it is necessary to efficiently detect impending collisions between the manipulator and the workspace obstacles. A collision detection method is presented which is based upon two representations. The dynamic elements, such as the manipulator links, are modelled as sets of spheres. The static elements, such as the workspace obstacles, are represented as a weighted voxel map, in which the value of any voxel is indicative of its distance to the nearest obstacle. Combining these two representations results in a collision detection method which is obstacle count independent, i.e. independent of the number of obstacles in the workspace. This property is desirable for operation in cluttered environments with many obstacles, where the total number of calculations in the alternative collision detection paradigm of pairwise comparison will prohibit real-time performance. The method is efficient enough to satisfy a hard real-time constraint Novel algorithms are described to generate the voxel map and spherical model representations, and an implementation is described which uses the collision detection method for real-time teleoperated collision avoidance and online path planning of a Puma 560 manipulator.
['Michael A. Greenspan', 'Nestor Burtnyk']
Obstacle count independent real-time collision avoidance