Abstract
In physical Human-Robot Cooperation (pHRC), humans and robots interact frequently or continuously to manipulate the same object or workpiece. One of the tasks within pHRC that has the highest potential for increased value in the industry is the cooperative lifting (co-lift) task where humans and robots lift long, flexible or heavy objects together. For such tasks, it is important for both safety and control that the human and robot can access motion information of the other to safely and accurately execute tasks together. In this paper, we propose to use Inertial Measurement Units (IMUs) to estimate human motions for pHRC, and also to use the IMU motion data to identify two-arm gestures that can aid in controlling the human-robot cooperation. We show how to use pHRC leader-follower roles to exploit the human cognitive skills to easily locate the object to lift, and robot skills to accurately place the object on a predefined target location. The experimental results presented show how to divide the co-lifting operation into stages: approaching the object while clutching in and out of controlling the robot motions, cooperatively lift and move the object towards a new location, and place the object accurately on a predefined target location. We believe that the results presented in this paper have the potential to further increase the uptake of pHRC in the industry since the proposed approach do not require any pre-installation of a positioning system or features of the object to enable pHRC.
This work was funded by the Research Council of Norway through grant number 280771.
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Ateş, G., Kyrkjebø, E. (2021). Human-Robot Cooperative Lifting Using IMUs and Human Gestures. In: Fox, C., Gao, J., Ghalamzan Esfahani, A., Saaj, M., Hanheide, M., Parsons, S. (eds) Towards Autonomous Robotic Systems. TAROS 2021. Lecture Notes in Computer Science(), vol 13054. Springer, Cham. https://doi.org/10.1007/978-3-030-89177-0_9
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