Configuration Space Of Robot Research Articles

New heuristic algorithms for efficient hierarchical path planning

The authors consider one of the most popular approaches to path planning: hierarchical approximate cell decomposition. This approach consists of constructing successive decompositions of the robot's configuration space into rectangloid cells and searching the connectivity graph built at each level of decomposition for a path. Despite its conceptual simplicity, an efficient implementation of this approach raises many delicate questions that have not yet been addressed. The major contributions this work are (1) a novel approach to cell decomposition based on constraint reformulation and (2) a new algorithm for hierarchical search with a mechanism for recording failure conditions. These algorithms have been implemented in a path planner, and experiments with this planner have been carried out on various examples. These experiments show that the proposed planner is significantly (approximately 10 times) faster than previous planners based on the same general approach. >

Hierarchical Robot Control Including Fast Collision-Free Motion-Planning

A hierarchically structured multi-level control concept for industrial robot manipulators is presented, which is especially suited for task-level programming. This concept contains decentralized control of the manipulator's axes and superior levels concerning on-line collision avoidance and collision-free motion-planning, based on the task demands and sensor information about the environment. The paper concentrates on the presentation of a new fast algorithm for the planning of a manipulator's gross-motion, which enables the consideration of an environment with changing obstacles. Path-searching is performed in the robot's configuration-space, modelled as a graph with regular grid structure, by using an especially adapted searching algorithm. The efficiency of this method will be demonstrated by the use of a SCARA assembly robot.