Abstract
Tendon-driven robot manipulators are often used to actuate distal joints. The tendons allow the actuators to be located outside the fingers. Conventionally, the use of the tendons of the fingers allows for the significant reduction to the size and weight, in this case, which approximately similar to that of the human. To achieve the interaction with unstructured environments, a torque control system is presented based on the single neuron networks (SNN) in this paper. The torque control allows the system maintain proper torques on the joints. Meanwhile, this controller calculates actuator positions based on the error measured by the actual joint torques and desired joint torques. Simulations have been conducted on a tendon-driven finger model to demonstrate that the proposed controller can achieve the faster response, and then decrease overshoot comparing to a PI controller.
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Meng, M., Wang, X., Wang, X. (2017). Adaptive SNN Torque Control for Tendon-Driven Fingers. In: Fei, M., Ma, S., Li, X., Sun, X., Jia, L., Su, Z. (eds) Advanced Computational Methods in Life System Modeling and Simulation. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 761. Springer, Singapore. https://doi.org/10.1007/978-981-10-6370-1_23
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DOI: https://doi.org/10.1007/978-981-10-6370-1_23
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