An efficient and accurate force/torque sensing method based on an excitation trajectory

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 : 2023-02-17 DOI:10.1108/ir-08-2022-0206
K. Min, F. Ni, Hong Liu
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Abstract

Purpose The purpose of the paper is to propose an efficient and accurate force/torque (F/T) sensing method for the robotic wrist-mounted six-dimensional F/T sensor based on an excitation trajectory. Design/methodology/approach This paper presents an efficient and accurate F/T sensing method based on an excitation trajectory. First, the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity. Therefore, the sensing accuracy is improved. Then, the excitation trajectory with optimized poses is used for robot following and data acquisition. The data acquisition is not limited by poses and its time can be significantly shortened. Finally, the least squares method is used to identify parameters and sense contact forces/torques. Findings Experiments have been carried out on the self-developed robot manipulator. The results strongly demonstrate that the proposed approach is more efficient and accurate than the existing widely-adopted method. Furthermore, the data acquisition time can be shortened from more than 60 s to 3 s/20 s. Thus, the proposed approach is effective and suitable for fast-paced industrial applications. Originality/value The main contributions of this paper are as follows: the dynamic identification model is established by comprehensively considering inertial forces/torques, sensor zero-drift values, robot base inclination errors and forces/torques caused by load gravity; and the excitation trajectory with optimized poses is used for robot following and data acquisition.
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基于激励轨迹的高效、准确的力/扭矩传感方法
目的提出一种基于激励轨迹的机器人腕式六维力/扭矩传感器的高效、准确的力/扭矩传感方法。设计/方法/方法本文提出了一种基于激励轨迹的高效、精确的F/T传感方法。首先,综合考虑惯性力/力矩、传感器零漂移值、机器人基座倾角误差和负载重力引起的力/力矩,建立动态识别模型;因此,提高了传感精度。然后,利用优化后的激励轨迹进行机器人跟踪和数据采集。数据采集不受姿态限制,可显著缩短采集时间。最后,采用最小二乘法进行参数辨识和接触力/力矩检测。在自主研制的机械臂上进行了实验研究。结果表明,该方法比目前广泛采用的方法具有更高的效率和精度。数据采集时间从60秒以上缩短到3秒/20秒。因此,所提出的方法是有效的,适合于快节奏的工业应用。本文的主要贡献如下:综合考虑惯性力/力矩、传感器零漂移值、机器人基座倾角误差和负载重力引起的力/力矩,建立了机器人的动态识别模型;将优化后的激励轨迹用于机器人的跟踪和数据采集。
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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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