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Hybrid Feedback Control Design for Non-Convex Obstacle Avoidance (2304.10598v6)

Published 20 Apr 2023 in cs.RO, cs.SY, and eess.SY

Abstract: We develop an autonomous navigation algorithm for a robot operating in two-dimensional environments containing obstacles, with arbitrary non-convex shapes, which can be in close proximity with each other, as long as there exists at least one safe path connecting the initial and the target location. An instrumental transformation that modifies (virtually) the non-convex obstacles, in a non-conservative manner, is introduced to facilitate the design of the obstacle-avoidance strategy. The proposed navigation approach relies on a hybrid feedback that guarantees global asymptotic stabilization of a target location while ensuring the forward invariance of the modified obstacle-free workspace. The proposed hybrid feedback controller guarantees Zeno-free switching between the move-to-target mode and the obstacle-avoidance mode based on the proximity of the robot with respect to the modified obstacle-occupied workspace. Finally, we provide an algorithmic procedure for the sensor-based implementation of the proposed hybrid controller and validate its effectiveness via some numerical simulations.

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References (27)
  1. O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robots,” The International Journal of Robotics Research, pp. 90–98, 1986.
  2. D. E. Koditschek and E. Rimon, “Robot navigation functions on manifolds with boundary,” Advances in applied mathematics, vol. 11, no. 4, pp. 412–442, 1990.
  3. D. Koditschek and E. Rimon, “Exact robot navigation using artificial potential functions,” IEEE Trans. Robot. Automat, vol. 8, pp. 501–518, 1992.
  4. C. K. Verginis and D. V. Dimarogonas, “Adaptive robot navigation with collision avoidance subject to 2nd-order uncertain dynamics,” Automatica, vol. 123, p. 109303, 2021.
  5. C. Li and H. G. Tanner, “Navigation functions with time-varying destination manifolds in star worlds,” IEEE Transactions on Robotics, vol. 35, no. 1, pp. 35–48, 2018.
  6. S. Paternain, D. E. Koditschek, and A. Ribeiro, “Navigation functions for convex potentials in a space with convex obstacles,” IEEE Transactions on Automatic Control, vol. 63, no. 9, pp. 2944–2959, 2017.
  7. S. G. Loizou, “The navigation transformation: Point worlds, time abstractions and towards tuning-free navigation,” in 19th Mediterranean Conference on Control & Automation (MED), 2011, pp. 303–308.
  8. S. G. Loizou and E. D. Rimon, “Correct-by-construction navigation functions with application to sensor based robot navigation,” arXiv preprint arXiv:2103.04445, 2021.
  9. S. Berkane, “Navigation in unknown environments using safety velocity cones,” in American Control Conference, 2021, pp. 2336–2341.
  10. M. F. Reis, A. P. Aguiar, and P. Tabuada, “Control barrier function-based quadratic programs introduce undesirable asymptotically stable equilibria,” IEEE Control Systems Letters, vol. 5, no. 2, pp. 731–736, 2020.
  11. O. Arslan and D. E. Koditschek, “Sensor-based reactive navigation in unknown convex sphere worlds,” The International Journal of Robotics Research, vol. 38, no. 2-3, pp. 196–223, 2019.
  12. V. Vasilopoulos and D. E. Koditschek, “Reactive navigation in partially known non-convex environments,” in International Workshop on the Algorithmic Foundations of Robotics, 2018, pp. 406–421.
  13. C. Vrohidis, P. Vlantis, C. P. Bechlioulis, and K. J. Kyriakopoulos, “Prescribed time scale robot navigation,” IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 1191–1198, 2018.
  14. R. G. Sanfelice, M. J. Messina, S. E. Tuna, and A. R. Teel, “Robust hybrid controllers for continuous-time systems with applications to obstacle avoidance and regulation to disconnected set of points,” in American Control Conference, 2006, pp. 3352–3357.
  15. J. I. Poveda, M. Benosman, A. R. Teel, and R. G. Sanfelice, “Robust coordinated hybrid source seeking with obstacle avoidance in multivehicle autonomous systems,” IEEE Transactions on Automatic Control, vol. 67, no. 2, pp. 706–721, 2022.
  16. P. Braun, C. M. Kellett, and L. Zaccarian, “Explicit construction of stabilizing robust avoidance controllers for linear systems with drift,” IEEE Transactions on Automatic Control, vol. 66, no. 2, pp. 595–610, 2020.
  17. A. S. Matveev, H. Teimoori, and A. V. Savkin, “A method for guidance and control of an autonomous vehicle in problems of border patrolling and obstacle avoidance,” Automatica, vol. 47, no. 3, pp. 515–524, 2011.
  18. S. Berkane, A. Bisoffi, and D. V. Dimarogonas, “Obstacle avoidance via hybrid feedback,” IEEE Transactions on Automatic Control, vol. 67, no. 1, pp. 512–519, 2021.
  19. V. Lumelsky and A. Stepanov, “Dynamic path planning for a mobile automaton with limited information on the environment,” IEEE transactions on Automatic control, vol. 31, no. 11, pp. 1058–1063, 1986.
  20. S. G. Loizou, H. G. Tanner, V. Kumar, and K. J. Kyriakopoulos, “Closed loop motion planning and control for mobile robots in uncertain environments,” in IEEE Conference on Decision and Control, vol. 3, 2003, pp. 2926–2931.
  21. M. Sawant, S. Berkane, I. Polusin, and A. Tayebi, “Hybrid feedback for autonomous navigation in planar environments with convex obstacles,” IEEE Transaction on Automatic Control, vol. 68, no. 12, pp. 7342–7357, 2023.
  22. M. Sawant, A. Tayebi, and I. Polushin, “Autonomous navigation in environments with arbitrary non-convex obstacles,” in IEEE Conference on Decision and Control, 2022, pp. 7208–7213.
  23. R. M. Haralick, S. R. Sternberg, and X. Zhuang, “Image analysis using mathematical morphology,” IEEE transactions on pattern analysis and machine intelligence, no. 4, pp. 532–550, 1987.
  24. J. Serra, “Introduction to mathematical morphology,” Computer vision, graphics, and image processing, vol. 35, no. 3, pp. 283–305, 1986.
  25. C. Thäle, “50 years sets with positive reach–a survey.” Surveys in Mathematics and its Applications, vol. 3, pp. 123–165, 2008.
  26. I. Kamon, E. Rimon, and E. Rivlin, “Tangentbug: A range-sensor-based navigation algorithm,” The International Journal of Robotics Research, vol. 17, no. 9, pp. 934–953, 1998.
  27. S. Berkane, A. Bisoffi, and D. V. Dimarogonas, “Obstacle avoidance via hybrid feedback,” arXiv preprint arXiv:2102.02883, 2021.
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