Genetic control of near time-optimal motion for an industrial robot arm

The search for the minimum-time path of a robotic manipulator graphically by tessellating the joint space involves heavy computational burden. Genetic algorithms (GAs) have been used to tackle this problem and have reduced the computational search time a great deal. The work presented here provides a practical GAs motion control for possible real-time implementations. A kind of heuristic search technique is found to be necessary to further reduce the search time. The end-velocity is dealt with by placing a penalty on the objective function. A scheme using a fifth order polynomial function to generate smooth initial path population is presented. Much better results with much less cost have been acquired than many of those reported earlier in the literature. Time-optimal motion for a six DOF robot arm is also included, which is made possible by using GAs. It has been found that the quickest motion is not necessarily a straight line in joint space.