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| DOI： |
| Received:June 05, 2004Revised:October 31, 2004 |
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| Novel integrated optimization algorithm for trajectory planning of robot manipulators based on integrated evolutionary programming |
| Xiong LUO, Xiaoping FAN, Heng ZHANG, Tefang CHEN |
| (College of Information Science and Engineering, Central South University, Changsha Hunan 410083, China) |
| Abstract: |
| Optimal trajectory planning for robot manipulators plays an important role in implementing the high productivity for robots. The performance indexes used in optimal trajectory planning are classified into two main categories: optimum traveling time and optimum mechanical energy of the actuators. The current trajectory planning algorithms are designed based on one of the above two performance indexes. So far, there have been few planning algorithms designed to satisfy two performance indexes simultaneously. On the other hand, some deficiencies arise in the existing integrated optimization algorithms of trajectory planning. In order to overcome those deficiencies, the integrated optimization algorithms of trajectory planning are presented based on the complete analysis for trajectory planning of robot manipulators. In the algorithm, two object functions are designed based on the specific weight coefficient method and "ideal point" strategy. Moreover, based on the features of optimization problem, the intensified evolutionary programming is proposed to solve the corresponding optimization model. Especially, for the Stanford Robot,the high-quality solutions are found at 3 lower cost. |
| Key words: Trajectory planning Integrated optimization Evolutionary programming Robot manipulator |
