Randomized parallel motion planning for robot manipulators

We present a novel approach to parallel motion planning for robot manipulators in 3D workspaces. The approach is based on a randomized parallel search algorithm and focuses on solving the path planning problem for industrial robot arms working in a reasonably cluttered workspace.The path planning system works in the discretized configuration space, which needs not to be represented explicitly. The parallel search is conducted by a number of rule-based sequential search processes, which work to find a path connecting the initial configuration to the goal via a number of randomly generated subgoal configurations. Since the planning performs only on-line collision tests with proper proximity information without using pre-computed information, the approach is suitable for planning problems with multirobot or dynamic environments. The implementation has been carried out on the parallel virtual machine (PVM) of a cluster of SUN4 workstations and SGI machines. The experimental results have shown that the approach works well for a 6-dof robot arm in a reasonably cluttered environment, and that parallel computation increases the efficiency of motion planning significantly

Path planning for industrial robot arms - A parallel randomized approach

The paper presents a novel approach to parallel motion planning for robot manipulators in 3D workspaces. The approach is based on a randomized parallel search algorithm and focuses on solving the path planning problem for industrial robot arms working in a reasonably cluttered workspace. The path planning system works in the discretized configuration space which needs not to be represented explicitly. The parallel search is conducted by a number of rule-based sequential search processes, which work to nd a path connecting the initial configuration to the goal via a number of randomly generated subgoal configurations. Since the planning performs only on-line collision tests with proper proximity information without using pre-computed information, the approach is suitable for planning problems with multirobot or dynamic environments. The implementation has been carried out on the parallel virtual machine (PVM) of a cluster of SUN4 workstations and SGI machines. The experimental results have shown that the approach works well for a 6-dof robot arm in a reasonably cluttered environment, and that parallel computation increases the efficiency of motion planning significantly

Randomized Parallel Motion Planning for Robot Manipulators

We have presented a novel approach to parallel motion planning for robot manipulators in 3D workspaces. The approach is based on arandomized parallel search algorithm and focuses on solving the path planning problem for industrial robot arms working in a reasonably cluttered workspace. The path planning system works in the discretized con guration space, which needs not to be represented explicitly. The parallel search is conducted by a number of rule-based sequential search processes, which work to find a path connecting the initial con guration to the goal via a number of randomly generated subgoal con gurations. Since the planning performs only on-line collision tests with proper proximity information without using pre-computed information, the approach is suitable for planning problems with multirobot or dynamic environments. The implementation has been carried outontheparallel virtual machine (PVM) of a cluster of SUN4 workstations and SGI machines. The experimental results have shown that the approach works well for a 6-dof robot arm in a reasonably cluttered environment, and that parallel computation increases the e ciency of motion planning signi cantly

D.: "Path planning for industrial robot arms - A parallel randomized approach

Abstract. The paper presents a novel approach to parallel motion planning for robot manipulators in 3D workspaces. The approach is based on a randomized parallel search algorithm and focuses on solving the path planning problem for industrial robot arms working in a reasonably cluttered workspace. The path planning system works in the discretized con guration space which needs not to be represented explicitly. The parallel search is conducted by anumber of rule-based sequential search processes, which work to nd a path connecting the initial con guration to the goal via a number of randomly generated subgoal con gurations. Since the planning performs only on-line collision tests with proper proximity information without using pre-computed information, the approach is suitable for planning problems with multirobot or dynamic environments. The implementation has been carried out on the parallel virtual machine (PVM) of a cluster of SUN4 workstations and SGI machines. The experimental results haveshown that the approachworks well for a 6-dof robot arm in a reasonably cluttered environment, and that parallel computation increases the e ciency of motion planning signi cantly.

Randomized Parallel Motion Planning for Robot Manipulators

We have presented a novel approach to parallel motion planning for robot manipulators in 3D workspaces. The approach is based on a randomized parallel search algorithm and focuses on solving the path planning problem for industrial robot arms working in a reasonably cluttered workspace. The path planning system works in the discretized configuration space, which needs not to be represented explicitly. The parallel search is conducted by a number of rule-based sequential search processes, which work to find a path connecting the initial configuration to the goal via a number of randomly generated subgoal configurations. Since the planning performs only on-line collision tests with proper proximity information without using pre-computed information, the approach is suitable for planning problems with multirobot or dynamic environments. The implementation has been carried out on the parallel virtual machine (PVM) of a cluster of SUN4 workstations and SGI machines. The experimental results..

Motion Planning and Collision Avoidance with Complex Geometry

CAD and robot simulation tools are often used to verify a workcell or process at the design phase: a geometric model of the machinery involved is produced, and pictures of the model examined for potential problems. However more advanced techniques for collision detection and path planning are only slowly filtering out of the research laboratories. We introduce a path planning shell called OxSim that is based on the separation of geometry and planning. We claim that OxSim makes it much easier to prototype collision detection and path planning schemes involving large and complex geometries, and outline how that system has been used up to now, and our plans for further research. Keywords Robot simulation, path planning, collision detection, distance computation. 1 Introduction The ability to perform fast path planning is a useful skill for a robot working in a hazardous environment. However, although path planning has been a research field for many years the use of the techniques of ..