Collision risk assessment and automatic obstacle avoidance strategy for teleoperation robots. (July 2022) - Pan, Mingzhang; Li, Jing; Yang, Xiuze; Wang, Shuo; Pan, Lei; Su, Tiecheng; Wang, Yuke; Yang, Qiye; Liang, Ke
Highlights: Collision risk models take into account distance, speed and some indirect factors. Convert the impact of speed on a collision into a measure of distance. The discretization method is used to calculate the collision risk value. Hierarchical design of obstacle avoidance strategies based on collision risk. The collision risk threshold will change with some external factors. Abstract: Teleoperation robots have been paid more attention in aerospace, medical domain, and other fields because of their high precision and maneuverability. However, the working environments in these fields are characterized by danger or complexity, which require the high collision avoidance ability of teleoperation robots. Therefore, it is necessary to conduct in-depth research on collision and obstacle avoidance problems of teleoperation robots. Based on this goal, a new model of quantifying collision risk is proposed to solve the problem that traditional collision risk assessment is inaccurate due to incomplete consideration of factors. The model considers not only the common factor likes distance but also a relatively newer factor, i.e. speed. In addition, the effect of indirect factors such as work environment and robot system on collision are innovatively considered. Some innovative modifications are made to the calculation method of the model. The effect of speed on collision is studied by using distance, and the discretization method is introduced to calculate the collision risk value. Secondly, in order to improve the existing obstacle avoidance strategies are not perfect enough, a new set of automatic obstacle avoidance strategies for teleoperation robots is proposed based on collision risk. The collision risk value can be classified into three levels according to collision risk threshold, and each level has different obstacle avoidance strategies to make obstacle avoidance more reasonable and effective. Finally, the proposed collision risk model and the automatic obstacle avoidance strategy are verified. The results show that the proposed collision risk model can accurately quantify the collision situation of the robot, and the proposed automatic obstacle avoidance strategy can keep the robot away from the obstacles when moving, thereby achieving the purpose of obstacle avoidance. In general, this study provides an effective method for collision risk assessment and automatic obstacle avoidance of teleoperation robots.