Judgment method of grasping stability for dexterous hand based on force balance theorem and Monte Carlo method

IF 1.9 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL Industrial Robot-The International Journal of Robotics Research and Application Pub Date : 2022-09-08 DOI:10.1108/ir-05-2022-0125
Yinghan Wang, Diansheng Chen, Zhe Liu
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Abstract

Purpose Multi-sensor fusion in robotic dexterous hands is a hot research field. However, there is little research on multi-sensor fusion rules. This study aims to introduce a multi-sensor fusion algorithm using a motor force sensor, film pressure sensor, temperature sensor and angle sensor, which can form a consistent interpretation of grasp stability by sensor fusion without multi-dimensional force/torque sensors. Design/methodology/approach This algorithm is based on the three-finger force balance theorem, which provides a judgment method for the unknown force direction. Moreover, the Monte Carlo method calculates the grasping ability and judges the grasping stability under a certain confidence interval using probability and statistics. Based on three fingers, the situation of four- and five-fingered dexterous hand has been expanded. Moreover, an experimental platform was built using dexterous hands, and a grasping experiment was conducted to confirm the proposed algorithm. The grasping experiment uses three fingers and five fingers to grasp different objects, use the introduced method to judge the grasping stability and calculate the accuracy of the judgment according to the actual grasping situation. Findings The multi-sensor fusion algorithms are universal and can perform multi-sensor fusion for multi-finger rigid, flexible and rigid-soft coupled dexterous hands. The three-finger balance theorem and Monte Carlo method can better replace the discrimination method using multi-dimensional force/torque sensors. Originality/value A new multi-sensor fusion algorithm is proposed and verified. According to the experiments, the accuracy of grasping judgment is more than 85%, which proves that the method is feasible.
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基于力平衡定理和蒙特卡罗法的灵巧手抓取稳定性判断方法
目的机器人灵巧手的多传感器融合是一个研究热点。然而,对多传感器融合规则的研究却很少。本研究旨在介绍一种利用电机力传感器、薄膜压力传感器、温度传感器和角度传感器的多传感器融合算法,该算法可以在没有多维力/扭矩传感器的情况下,通过传感器融合形成抓取稳定性的一致解释。该算法基于三指力平衡定理,为未知的力方向提供了一种判断方法。蒙特卡罗方法计算抓取能力,并在一定置信区间内利用概率统计判断抓取稳定性。在三指的基础上,扩展了四指和五指灵巧手的情况。利用灵巧手搭建了实验平台,并进行了抓握实验,验证了该算法的有效性。抓取实验采用三指和五指抓取不同的物体,利用所介绍的方法对抓取稳定性进行判断,并根据实际抓取情况计算判断的准确性。结果多传感器融合算法具有通用性,可实现多指刚性、柔性和刚软耦合灵巧手的多传感器融合。三指平衡定理和蒙特卡罗方法可以较好地取代使用多维力/扭矩传感器的判别方法。提出并验证了一种新的多传感器融合算法。实验结果表明,抓取判断准确率达85%以上,证明了该方法的可行性。
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来源期刊
CiteScore
4.50
自引率
16.70%
发文量
86
审稿时长
5.7 months
期刊介绍: Industrial Robot publishes peer reviewed research articles, technology reviews and specially commissioned case studies. Each issue includes high quality content covering all aspects of robotic technology, and reflecting the most interesting and strategically important research and development activities from around the world. The journal’s policy of not publishing work that has only been tested in simulation means that only the very best and most practical research articles are included. This ensures that the material that is published has real relevance and value for commercial manufacturing and research organizations. Industrial Robot''s coverage includes, but is not restricted to: Automatic assembly Flexible manufacturing Programming optimisation Simulation and offline programming Service robots Autonomous robots Swarm intelligence Humanoid robots Prosthetics and exoskeletons Machine intelligence Military robots Underwater and aerial robots Cooperative robots Flexible grippers and tactile sensing Robot vision Teleoperation Mobile robots Search and rescue robots Robot welding Collision avoidance Robotic machining Surgical robots Call for Papers 2020 AI for Autonomous Unmanned Systems Agricultural Robot Brain-Computer Interfaces for Human-Robot Interaction Cooperative Robots Robots for Environmental Monitoring Rehabilitation Robots Wearable Robotics/Exoskeletons.
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