Collaborative Assembly in Hybrid Manufacturing Cells: An Integrated Framework for Human–Robot Interaction

Abstract

Recent emergence of safe, lightweight, and flexible robots has opened a new realm for human–robot collaboration in manufacturing. Utilizing such robots with the new human–robot interaction (HRI) functionality to interact closely and effectively with a human co-worker, we propose a novel framework for integrating HRI factors (both physical and social interactions) into the robot motion controller for human–robot collaborative assembly tasks in a manufacturing hybrid cell. To meet human physical demands in such assembly tasks, an optimal control problem is formulated for physical HRI (pHRI)-based robot motion control to keep pace with human motion progress. We further augment social HRI (sHRI) into the framework by considering a computational model of the human worker’s trust in his/her robot partner as well as robot facial expressions. The human worker’s trust in robot is computed and used as a metric for path selection as well as a constraint in the optimal control problem. Robot facial expression is displayed for providing additional visual feedbacks to the human worker. We evaluate the proposed framework by designing a robotic experimental testbed and conducting a comprehensive study with a human-in-the-loop. Results of this paper show that compared to the manual adjustments of robot velocity, an autonomous controller based on pHRI, pHRI and sHRI with trust, or pHRI and sHRI with trust, and emotion result in 34%, 39%, and 44% decrease in human workload and 21%, 32%, and 60% increase in robot’s usability, respectively. Compared to the manual framework, human trust in robot increases by 38% and 42%, respectively, in the latter two autonomous frameworks. Moreover, the overall efficiency in terms of assembly time remains the same. Note to Practitioners —Conventionally, industrial robots are used to perform repetitive tasks in human-free cages with minimal HRI for safety concerns. Thanks to the new safety and flexibility functions embedded in human-friendly manufacturing robots, humans and robots can now collaborate closely with each other accomplishing the tasks that were previously done by human workers solely. However, existing criteria for designing robot controllers need to be modified by considering the human workers’ demands since the performance of a human worker would vary due to factors such as individual strength, working pattern, and interaction with the robot. To address this problem, we propose a novel framework that integrates HRI factors in controlling the motion of a robot for the collaborative assembly tasks. Within this framework, the speed of robot can be controlled such that its motion progress synchronizes with that of the human during the task to improve pHRI. Moreover, for better sHRI, human trust in robot is calculated and used to select robot path and modify its speed control. Furthermore, we dynamically change the robot facial expression to provide visual feedbacks for performance and safety concerns. The results of the experimental study show that integrating both pHRI and sHRI in the robot controller leads to a significant drop of human perceived workload and considerable increase of robot usability and human trust in robot while the overall efficiency in terms of assembly time remains intact. For practical utilization in assembly plants, sensory devices for tracking the human motion are required. The robot is also required to have built-in safety functions that reduce the impact of possible collisions between the human and the robot. We believe that this paper addresses how the implementation of human-friendly robots in the manufacturing environments can improve HRI and reduce workload.