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Adaptive Robotic Levering for Recycling Tasks

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Advances in Service and Industrial Robotics (RAAD 2023)

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 135))

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Abstract

A common step in autonomous robotic disassembly (recycling) of electronics is levering, which allows the robot to apply greater forces when removing parts of the devices. In practical applications, the robot should be able to adapt a levering action to different device types without an operator specifically recording a trajectory for each device. A method to generalize the existing levering actions to new devices is thus needed. In this paper we present a parameterized algorithm for performing robotic levering using feedback-based control to determine contact points and a sinusoidal pattern to realize adaptive levering motion. The algorithm can deal with devices of different shapes. After the initial adaptation process, the subsequent executions of the learnt levering action can be sped up to improve performance.

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References

  1. Foo, G., Kara, S., Pagnucco, M.: Challenges of robotic disassembly in practice. Proc. CIRP 105, 513–518 (2022)

    Article  Google Scholar 

  2. Gašpar, T., et al.: Smart hardware integration with advanced robot programming technologies for efficient reconfiguration of robot workcells. Robot. Comput.-Integr. Manuf. 66, 101979 (2020)

    Google Scholar 

  3. Simonič, M., Petrič, T., Ude, A., Nemec, B.: Analysis of methods for incremental policy refinement by kinesthetic guidance. J. Intell. Robot. Syst. 102 (2021)

    Google Scholar 

  4. Laili, Y., Wang, Y., Fang, Y., Pham, D.: Optimisation of Robotic Disassembly for Remanufacturing (2022)

    Google Scholar 

  5. Radanovič, P., Jereb, J., Kovač, I., Ude, A.: Design of a modular robotic workcell platform enabled by plug & produce connectors. In: 2021 20th International Conference on Advanced Robotics (ICAR), pp. 304–309 (2021)

    Google Scholar 

  6. Gams, A., Do, M., Ude, A., Asfour, T., Dillmann, R.: On-line periodic movement and force-profile learning for adaptation to new surfaces. In: 2010 10th IEEE-RAS International Conference on Humanoid Robots, pp. 560–565 (2010)

    Google Scholar 

  7. Kroemer, O., Niekum, S., Konidaris, G.: A review of robot learning for manipulation: challenges, representations, and algorithms. J. Mach. Learn. Res. 22(1), 1395–1476 (2021)

    MathSciNet  MATH  Google Scholar 

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Correspondence to Boris Kuster .

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Kuster, B., Simonič, M., Ude, A. (2023). Adaptive Robotic Levering for Recycling Tasks. In: Petrič, T., Ude, A., Žlajpah, L. (eds) Advances in Service and Industrial Robotics. RAAD 2023. Mechanisms and Machine Science, vol 135. Springer, Cham. https://doi.org/10.1007/978-3-031-32606-6_49

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