期刊
IEEE ACCESS
卷 8, 期 -, 页码 54225-54236出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.2981688
关键词
Motion planning; dual robotic manipulators; dynamic neural networks; zeroing neural networks; redundant resolution
资金
- National Key Research and Development Program of China [2017YFB1300200]
- Natural Sciences Foundation of Guangdong China [2017A030313690]
- Guangdong Province Key Areas Research and Development Program [2019B090919002]
- Department of Education of Guangdong China [2017KZDXM082]
- Guangzhou Science and Technology Plan Project [201803010106]
- GDAS Project of Thousand doctors (postdoctors) Introduction [2019GDASYL-0103078]
- GDAS Project of Science and Technology Development [2020GDASYL-20200402007]
- Guangdong Basic and Applied Basic Research Foundation [2020A1515010631]
- Dongguan Social Science and Technology Development Project [2019507140209]
Dual robotic manipulators are robotic systems that are developed to imitate human arms, which shows great potential in performing complex tasks. Collision-free motion planning in real time is still a challenging problem for controlling a dual robotic manipulator because of the overlap workspace. In this paper, a novel planning strategy under physical constraints of dual manipulators using dynamic neural networks is proposed, which can satisfy the collision avoidance and trajectory tracking. Particularly, the problem of collision avoidance is first formulated into a set of inequality formulas, whereas the robotic trajectory is then transformed into an equality constraint by introducing negative feedback in outer loop. The planning problem subsequently becomes a Quadratic Programming (QP) problem by considering the redundancy, the boundaries of joint angles and velocities of the system. The QP is solved using a convergent provable recurrent neural network that without calculating the pseudo-inversion of the Jacobian. Consequently, numerical experiments on 8-DoF modular robot and 14-DoF Baxter robot are conducted to show the superiority of the proposed strategy.
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