Abstract
This paper presents an implementation and experimental validation of an algorithm for collision detection for industrial robots performing repetitive tasks. Collisions are detected by using two decision rules, one of which compares current-based estimated torques with previously calculated reference limits, while the second rule detects changes in torque dynamics. Reference limits represent experimentally acquired torque values processed in order to determine measurement tolerances based on dynamics of the signal, as well as to adapt to different sampling times. The main contribution of the paper is the algorithm which is entirely implemented on robot’s controller with closed control architecture, and only requires PC for initial offline processing of reference torques. It can be adapted for use on various brands of industrial robots, and it is universal to different robot configurations.
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Acknowledgment
The work on this project was partly supported by the Ministry of education, science, and technological development, Republic of Serbia, grant No. TR35003.
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Gordić, Z., Jovanović, K. (2019). Fully Integrated Torque-Based Collision Detection in Periodic Tasks for Industrial Robots with Closed Control Architecture. In: Aspragathos, N., Koustoumpardis, P., Moulianitis, V. (eds) Advances in Service and Industrial Robotics. RAAD 2018. Mechanisms and Machine Science, vol 67. Springer, Cham. https://doi.org/10.1007/978-3-030-00232-9_8
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DOI: https://doi.org/10.1007/978-3-030-00232-9_8
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