Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Robot motion planning: a distributed representation approach
International Journal of Robotics Research
An algorithm for planning collision-free paths among polyhedral obstacles
Communications of the ACM
A Parallel Collision-Avoidance Algorithm for Robot Manipulators
IEEE Concurrency
Spatial Planning: A Configuration Space Approach
IEEE Transactions on Computers
Complexity of the mover's problem and generalizations
SFCS '79 Proceedings of the 20th Annual Symposium on Foundations of Computer Science
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In this paper, a hierarchical evolutionary algorithm is proposed for the path planning of manipulators. The proposed algorithm consists of a global path planner (GPP) and a local motion planner (LMP). The global planner, a MAKLINK based approach, plans a trajectory for a robot end-effector from a starting free-space to goal free-space. An evolutionary algorithm with a non-random initial population is adopted to plan the manipulator configurations along a path given by the former stage. Once the optimal configuration is obtained by the evolutionary algorithm, the optimal chromosomes will be reserved as the initial population. Since the initial population is non-random, the evolution is more efficient and the planned path is smoother than traditional GA. Simulation results show that the proposed algorithm works well, specifically in terms of collision avoidance and computation efficiency.