The collision detection algorithm of the robot body previously needed to rely on the surface geometry information of the colliding object and no deformation was allowed during the collision process. To solve this problem, a new robot body collision detection algorithm that uses the force information of the six-axis force/torque sensor at the base to self-constrain is proposed which does not rely on the geometric information of the colliding object surface, and the deformation also allows deformation during the collision. In terms of sensor data preprocessing, a gravity and dynamic force compensation algorithm for the six-axis force/torque sensor at the base is proposed to ensure that the reading of the six-axis force/torque sensor at the base always maintains the value of 0 when the robot is working. Then, the robot is considered to have collided with the outside world when the sensor reading exceeds the set threshold. And a precision factor is proposed to analyze the influence of force and collision distance on the accuracy of the algorithm. Finally, the new algorithm proposed in this paper is compared with the traditional algorithm that relies on the geometric information of the colliding body surface. The experimental results indicate that the accuracy of the collision point detection algorithm proposed in this paper is close to that of the traditional method, but it does not need to rely on the geometric information of the collision body surface, and there is no requirement for whether there is deformation during the contact process. It can be concluded that the collision distance is the most important factor affecting the accuracy of the algorithm, followed by the conclusion of the magnitude of the collision force through the calculation of the precision factor. The results show that this method can effectively detect the collision point of the machine body, and the maximum error at the farthest point of the robot is 8.712%, which lays a certain foundation for the subsequent research on human-machine collaboration in small collaborative robots.

中文翻译：

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基于六轴力/扭矩传感器的碰撞点识别研究

机器人身体的碰撞检测算法以前需要依赖于碰撞对象的表面几何信息，并且在碰撞过程中不允许变形。为了解决这个问题，提出了一种新的机器人身体碰撞检测算法，该算法利用基础上的六轴力/扭矩传感器的力信息进行自约束，该算法不依赖于碰撞对象表面的几何信息，并且变形还允许碰撞过程中变形。在传感器数据预处理方面，提出了针对基座上的六轴力/扭矩传感器的重力和动态力补偿算法，以确保基座上的六轴力/扭矩传感器的读数始终保持值。机器人工作时为0。然后，如果传感器读数超过设定的阈值，则认为机器人与外界发生了碰撞。提出了一个精度因子来分析力和碰撞距离对算法精度的影响。最后，将本文提出的新算法与依赖于碰撞体表面几何信息的传统算法进行了比较。实验结果表明，本文提出的碰撞点检测算法的精度与传统方法相近，但不需要依赖碰撞体表面的几何信息，也就不需要接触过程中有变形。可以得出结论，碰撞距离是影响算法精度的最重要因素，其次是通过计算精度因子得出碰撞力的大小。结果表明，该方法能够有效地检测出机体的碰撞点，机器人最远处的最大误差为8.712％，为后续的小型协作机器人人机协作研究奠定了一定的基础。 。