Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
97 tokens/sec
GPT-4o
53 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
5 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Smoothly Connected Preemptive Impact Reduction and Contact Impedance Control (2212.03545v2)

Published 7 Dec 2022 in cs.RO

Abstract: This study proposes novel control methods that lower impact force by preemptive movement and smoothly transition to conventional contact impedance control. These suggested techniques are for force control-based robots and position/velocity control-based robots, respectively. Strong impact forces have a negative influence on multiple robotic tasks. Recently, preemptive impact reduction techniques that expand conventional contact impedance control by using proximity sensors have been examined. However, a seamless transition from impact reduction to contact impedance control has not yet been accomplished. The proposed methods utilize a serial combined impedance control framework to solve this problem. The preemptive impact reduction feature can be added to the already implemented impedance controller because the parameter design is divided into impact reduction and contact impedance control. There is no undesirable contact force during the transition. Furthermore, even though the preemptive impact reduction employs a crude optical proximity sensor, the influence of reflectance is minimized using a virtual viscous force. Analyses and real-world experiments confirm these benefits.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (28)
  1. R. Alexander et al., “Three uses for springs in legged locomotion,” Int. J. Robot. Res., vol. 9, no. 2, pp. 53–61, 1990.
  2. J. J. Rond, M. C. Cardani, M. I. Campbell, and J. W. Hurst, “Mitigating peak impact forces by customizing the passive foot dynamics of legged robots,” J. Mech. Robot., vol. 12, no. 5, p. 051010, 2020.
  3. G. De Magistris, S. Miossec, A. Escande, and A. Kheddar, “Design of optimized soft soles for humanoid robots,” Robot. Auton. Syst., vol. 95, pp. 129–142, 2017.
  4. A. Pajon, S. Caron, G. De Magistri, S. Miossec, and A. Kheddar, “Walking on gravel with soft soles using linear inverted pendulum tracking and reaction force distribution,” in Proc. Int. Conf. Humanoid Robot. (Humanoids), 2017, pp. 432–437.
  5. J. H. Park and H. Chung, “Hybrid control for biped robots using impedance control and computed-torque control,” in Proc. Int. Conf. Robot. Autom. (ICRA), vol. 2, 1999, pp. 1365–1370.
  6. C. Ott, A. Albu-Schaffer, A. Kugi, and G. Hirzinger, “On the passivity-based impedance control of flexible joint robots,” IEEE Trans. Robot., vol. 24, no. 2, pp. 416–429, 2008.
  7. S. K. Au, J. Weber, and H. Herr, “Powered ankle–foot prosthesis improves walking metabolic economy,” IEEE Trans. Robot., vol. 25, no. 1, pp. 51–66, 2009.
  8. A. Lecours, B. Mayer-St-Onge, and C. Gosselin, “Variable admittance control of a four-degree-of-freedom intelligent assist device,” in Proc. Int. Conf. Robot. Autom. (ICRA), 2012, pp. 3903–3908.
  9. F. Ficuciello, L. Villani, and B. Siciliano, “Variable impedance control of redundant manipulators for intuitive human–robot physical interaction,” IEEE Trans. Robot., vol. 31, no. 4, pp. 850–863, 2015.
  10. W. Huo, H. Moon, M. A. Alouane, V. Bonnet, J. Huang, Y. Amirat, R. Vaidyanathan, and S. Mohammed, “Impedance modulation control of a lower-limb exoskeleton to assist sit-to-stand movements,” IEEE Trans. Robot., vol. 38, no. 2, pp. 1230–1249, 2022.
  11. R. Sato, H. Arita, and A. Ming, “Pre-landing control for a legged robot based on tiptoe proximity sensor feedback,” IEEE Access, vol. 10, pp. 21 619–21 630, 2022.
  12. J. R. Guadarrama-Olvera, S. Kajita, and G. Cheng, “Preemptive foot compliance to lower impact during biped robot walking over unknown terrain,” IEEE Robot. Autom. Lett., vol. 7, no. 3, pp. 8006–8011, 2022.
  13. S. E. Navarro, S. Mühlbacher-Karrer, H. Alagi, H. Zangl, K. Koyama, B. Hein, C. Duriez, and J. R. Smith, “Proximity perception in human-centered robotics: A survey on sensing systems and applications,” IEEE Trans. Robot., vol. 38, no. 3, pp. 1599–1620, 2022.
  14. T. Fujiki and K. Tahara, “Numerical simulations of a novel force controller serially combining the admittance and impedance controllers,” in Proc. Int. Conf. Robot. Autom. (ICRA), 2021, pp. 6955–6962.
  15. N. Hogan, “Impedance control part 1-part 3,” Trans. of ASME, J. Dyn. Syst. Meas. Cont., vol. 107, pp. 1–24, 1985.
  16. K. Kosuge, K. Furuta, and T. Yokoyama, “Mechanical impedence control of a robot arm by virtual internal model following controller,” IFAC Proc. Vol., vol. 20, no. 5, pp. 239–244, 1987.
  17. C. Ott, R. Mukherjee, and Y. Nakamura, “A hybrid system framework for unified impedance and admittance control,” J. Intell. Robot. Syst., vol. 78, no. 3, pp. 359–375, 2015.
  18. T. Tsuji and M. Kaneko, “Noncontact impedance control for redundant manipulators,” IEEE Trans. Syst. Man Cybern. – Part A: Syst. Humans, vol. 29, no. 2, pp. 184–193, 1999.
  19. S.-Y. Lo, C.-A. Cheng, and H.-P. Huang, “Virtual impedance control for safe human-robot interaction,” J. Intell. Robot. Syst., vol. 82, no. 1, pp. 3–19, 2016.
  20. G. Cheng, E. Dean-Leon, F. Bergner, J. R. G. Olvera, Q. Leboutet, and P. Mittendorfer, “A comprehensive realization of robot skin: Sensors, sensing, control, and applications,” Proc. IEEE, vol. 107, no. 10, pp. 1–18, 2019.
  21. K. Koyama, K. Murakami, T. Senoo, M. Shimojo, and M. Ishikawa, “High-speed, small-deformation catching of soft objects based on active vision and proximity sensing,” IEEE Robot. Autom. Lett., vol. 4, no. 2, pp. 578–585, 2019.
  22. K. Koyama, Y. Suzuki, A. Ming, and M. Shimojo, “Grasping control based on time-to-contact method for a robot hand equipped with proximity sensors on fingertips,” in Proc. Int. Conf. Intell. Robot. Syst. (IROS), 2015, pp. 504–510.
  23. H. Arita and Y. Suzuki, “Contact transition control by adjusting emitting energy of proximity sensor,” Adv. Robot., vol. 35, no. 2, pp. 93–107, 2021.
  24. Y. Ding and U. Thomas, “Improving safety and accuracy of impedance controlled robot manipulators with proximity perception and proactive impact reactions,” in Proc. Int. Conf. Robot. Autom. (ICRA), 2021, pp. 3816–3821.
  25. ——, “Collision avoidance with proximity servoing for redundant serial robot manipulators,” in Proc. Int. Conf. Robot. Autom. (ICRA), 2020, pp. 10 249–10 255.
  26. A. R. Johnston, “Optical proximity sensors for manipulators,” JPL TM, pp. 33–612, 1973.
  27. E. Cheung and V. Lumelsky, “Development of sensitive skin for a 3d robot arm operating in an uncertain environment,” in Proc. Int. Conf. Robot. Autom. (ICRA), vol. 2, 1989, pp. 1056–1061.
  28. Y. Suzuki, “Proximity-based non-contact perception and omnidirectional point-cloud generation based on hierarchical information on fingertip proximity sensors,” Adv. Robot., vol. 35, no. 20, pp. 1181–1197, 2021.
User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (4)
  1. Hikaru Arita (4 papers)
  2. Hayato Nakamura (2 papers)
  3. Takuto Fujiki (1 paper)
  4. Kenji Tahara (5 papers)
Citations (2)
View on Semantic Scholar

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now