Task scheduling and motion planning for an industrial manipulator
We propose a method for robot planning and scheduling along given task-points. Optimization for multi-goal motion planning is solved through a Genetic Algorithm. Obstacle avoidance is achieved through the Bump-Surface concept. A PUMA 560 is used in 3 different 3D industrial environments to validate the method. Increasing the number of task-points or obstacles will increase CPU time.
task scheduling motion planning industrial manipulators genetic algorithm bump-surface