| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 413978 | Robotics and Computer-Integrated Manufacturing | 2013 | 14 Pages |
•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.
In many robotic industrial applications, a manipulator should move among obstacles and reach a set of task-points in order to perform a pre-defined task. It is quite important as well as very complicated to determine the time-optimum sequence of the task-points visited by the end-effector's tip only once assuring that the manipulator's motion through the successive task-points is collision-free.This paper introduces a method for simultaneously planning collision-free motion and scheduling time-optimal route along a set of given task-points. This method is based on the projection of the workspace and the robot on the B-Surface to formulate an objective function for the minimization of the cycle time in visiting multiple task-points and taken into account the multiple solutions of the inverse kinematics and the obstacle avoidance. A modified GA with special encoding to encounter the multiplicity of the robot inverse kinematics and the required intermediate configurations is used for the searching of the optimal solution on the B-Surface.The simulation results show the efficiency and the effectiveness of the proposed approach to determine a suboptimal tour for multi-goal motion planning in complex environments cluttered with obstacles.
