A recursive algorithm for on-line clustering obstacles cluttered in dynamic environments
In some applications of industrial robots, the robot manipulator must traverse a pre-specified Cartesian path with its hand tip while links of the robot safely move among obstacles cluttered in the robot's scene (environment). In order to reduce the costs of collision detection, one approach is to reduce the number of collision checks by enclosing a few real obstacles with a larger (artificial) bounding volume (a cluster), e.g., by their convex hull [4, 14], without cutting the specified path. In this paper, we propose a recursive algorithm composed of four procedures to tackle the problem of clustering convex polygons cluttered around a specified path in a dynamic environment. A key fact observed is that the number k of clusters is actually determined by the specified path not by any criterion used in clustering. Based on this fact, an initial set of k clusters could be rapidly generated. Then, the initial set of clusters and its number is further refined for satisfying the minimum Euclidean distance criterion imposed in clustering. Compared to the heuristic algorithm in [14], complexity of the proposed algorithm is reduced by one order with respect to the number n of obstacles. Simulation are performed in both static and dynamic environments, which show that the recursive algorithm is very efficient and acquires less number k of clusters.
on-line clustering dynamic environment collision detection convex polygons