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Virtual musculoskeletal control model with a spindle-like fuzzy algorithm for robotic compliance

机译:虚拟的肌肉骨骼控制模型,采用类似主轴的模糊算法来实现机器人柔顺性

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Robot manipulators should comply with the environment when working with humans. However, compliance control is a difficult problem for robots and thus it was investigated in the present study. We propose a virtual musculoskeletal control model from the perspective of bionics to facilitate the compliance of the robotic manipulator. The musculoskeletal system of the human forearm is simplified as a closed-loop control system with three parts: the central nervous system, muscles, and spindle. A mathematical model is deduced and integrated with the dynamic model of the robot manipulator. The control model also comprises three parts: the first part compensates for the Coriolis force and gravity; the second part provides stiffness to regulate the deviation; and the third part imitates the feedback from the spindle to comply with the environment. A fuzzy controller is designed based on the muscle and spindle model to obtain spindle-like feedback. Our simulation results demonstrate that the spindle-like fuzzy algorithm can adapt to the environmental constraints by imitating the function of the neural muscular system. This virtual musculoskeletal methodology allows accurate path control, but it also ensures the compliance of the robotic manipulator. These characteristics are helpful for allowing robot manipulators to cooperate with humans.
机译:与人类合作时,机器人操纵器应符合环境要求。但是,顺应性控制对于机器人来说是一个难题,因此在本研究中对其进行了研究。我们从仿生学的角度提出了虚拟的肌肉骨骼控制模型,以促进机器人操纵器的顺应性。人类前臂的肌肉骨骼系统被简化为具有三个部分的闭环控制系统:中枢神经系统,肌肉和纺锤体。推导了数学模型并将其与机器人机械手的动态模型集成在一起。控制模型还包括三个部分:第一部分补偿科里奥利力和重力。第二部分提供调节偏差的刚度;第三部分模仿主轴的反馈以符合环境要求。基于肌肉和纺锤体模型设计了模糊控制器,以获得纺锤体式的反馈。我们的仿真结果表明,类似主轴的模糊算法可以通过模仿神经肌肉系统的功能来适应环境约束。这种虚拟的肌肉骨骼方法可实现精确的路径控制,但也可确保机器人操纵器的顺从性。这些特征有助于使机器人操纵器与人类协作。

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