Enhanced Performance of Human-Robot Collaboration Using Braking Surfaces and Trajectory Scaling

Bakir Lacevic, Abdalla Reda Sobhy Ellithy Mahdy Newishy,Andrea Maria Zanchettin,Paolo Rocco

2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)(2023)

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摘要
This paper presents an effective approach to enable performance improvement in human-robot collaboration scenarios. The problem is tackled from the perspective of speed and separation monitoring principle, which stems from the recently instituted safety standard. The proposed approach attempts to seek for performance gains, measured by the speed-up of the production cycle, without compromising the safety constraints consistent with the standard. The approach is based on the notion of braking surface - an abstraction of the swept volume described by the manipulator during braking motion. We address two types of braking behavior: general and path-consistent. In both cases, the braking surface can be evaluated in a receding horizon manner. The robot velocity is continuously scaled such that, in case of a controlled stop, the corresponding volume spanned by the robot (braking surface) does not interfere with the surrounding obstacles. The approach is entirely kinematic and does not require the knowledge of the robot's dynamic model. Simulation study indicates that the proposed approach offers performance improvements compared to other state of the art methods. Moreover, the experiments demonstrate the real-time applicability of the method with the real robot in human-shared environment.
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