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Research on Obstacle-Avoidance Control Algorithm of Rehabilitation Robot Combined with Neural Network

机译:结合神经网络的康复机器人避障控制算法研究

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This paper proposes an obstacle-avoidance algorithm which can be applied to omnidirectional Lower Limbs Rehabilitation Robot. The method generates the attribute of obstacle scene using detected angle information of obstacle boundary, and fuzzy matching with the obstacle scene knowledgebase to realize the obstacle-avoidance control of robot. The implementation of fuzzy matching depends on fuzzy neural network. The neural network enhances self learning ability, greatly simplifies data calculation. Obstacle-avoidance algorithm makes the rehabilitation robot more safety for human using and reduces environmental using demand. This paper proves the feasibility and effectiveness of the obstacle-avoidance algorithm through theoretical derivation and simulation results.
机译:提出了一种可应用于全向下肢康复机器人的避障算法。该方法利用检测到的障碍物边界角度信息生成障碍物场景的属性,并与障碍物场景知识库进行模糊匹配,实现机器人的避障控制。模糊匹配的实现取决于模糊神经网络。神经网络增强了自我学习能力,大大简化了数据计算。避障算法使康复机器人对人类的使用更加安全,并减少了对环境的使用需求。通过理论推导和仿真结果证明了避障算法的可行性和有效性。

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