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New algorithm for estimation of reaction torque and compensation for elongation of wire for robotic forceps

机译:机器人钳的反作用力矩估计和钢丝伸长补偿的新算法。

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This paper proposes an algorithm that estimates a reaction torque loading the grasping jaws of wire-actuated robotic forceps and compensates for subsequent wire elongation. The algorithm is constructed by the combination of the Reaction Force Observer (RFOB) and an optimization problem based on a gradient descent method. The conventional RFOB is used to estimate an external torque that includes not only the reaction torque but also the acceleration of wire elongation. The wire elongation is directly obtained from the differential equation of wire elongation. Then, as a solution of the optimization problem, the acceleration of the wire elongation is obtained. Thus, the reaction torque is derived by subtracting the acceleration of wire elongation from the external torque estimated by the RFOB. Our previous algorithm required an assumption that the motor torque and reaction torque are constant, although they fluctuate in practice. The new algorithm eliminates this assumption, resulting much improved accuracy in estimating the reaction torque. The improvement was verified through simulation.
机译:本文提出了一种算法,该算法可估计负载在钢丝操纵的机器人钳的抓爪上的反作用转矩,并补偿随后的钢丝伸长。该算法由反作用力观测器(RFOB)与基于梯度下降法的优化问题相结合构造而成。传统的RFOB用于估计外部扭矩,该外部扭矩不仅包括反作用扭矩,还包括导线伸长的加速度。线伸长率是从线伸长率的微分方程直接获得的。然后,作为优化问题的解决方案,获得了金属丝伸长的加速。因此,反作用扭矩是通过从RFOB估算的外部扭矩中减去导线伸长的加速度得出的。我们先前的算法需要假设电动机转矩和反作用转矩是恒定的,尽管它们在实践中会波动。新算法消除了这一假设,从而大大提高了估计反作用扭矩的准确性。通过仿真验证了该改进。

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