Dynamic risk assessment and active response strategy of human-robot collaboration based on fuzzy comprehensive evaluation

Abstract

In the heavy-duty physical human-robot collaboration, the robot carries a large load and has a wide operating space and a complex operating environment. If the operator slips, trips or accidentally touches the obstacle, the body will lose balance, and the robot directly executes the operator's intent command will increase the degree of injury, and may even lead to dangerous situations such as workpiece collision and robot damage. Ensuring human operational safety is a prerequisite for achieving efficient collaborative tasks. Hence, it is imperative to approach this from the operator's perspective, ensuring that the robot conducts an operational intent risk assessment based on human motion characteristics before executing human-intended instructions. Subsequently, appropriate response strategies are implemented based on the assessment results to ensure the safety of human operations. Firstly, the human motion state data acquisition system is introduced; Secondly, based on the fuzzy comprehensive evaluation method, a risk assessment model was established by using multi-modal information to analyze three kinds of risk factors in motion; Thirdly, the robot's active response strategies for different risk levels are proposed; Finally, a risk assessment experiment of human-robot collaboration intention is carried out. The experimental results show that the robot using the proposed method can effectively detect abnormal behavior information of humans in the process of human-robot collaboration, and make corresponding decisions according to different levels of risk. It is of great significance for the application of heavy-duty physical human-robot collaboration in complex environments, and provides a way to achieve higher reliability and security in the field of physical human-robot collaboration.