Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
149 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Model-Based Planning and Control for Terrestrial-Aerial Bimodal Vehicles with Passive Wheels (2403.00322v1)

Published 1 Mar 2024 in cs.RO

Abstract: Terrestrial and aerial bimodal vehicles have gained widespread attention due to their cross-domain maneuverability. Nevertheless, their bimodal dynamics significantly increase the complexity of motion planning and control, thus hindering robust and efficient autonomous navigation in unknown environments. To resolve this issue, we develop a model-based planning and control framework for terrestrial aerial bi-modal vehicles. This work begins by deriving a unified dynamic model and the corresponding differential flatness. Leveraging differential flatness, an optimization-based trajectory planner is proposed, which takes into account both solution quality and computational efficiency. Moreover, we design a tracking controller using nonlinear model predictive control based on the proposed unified dynamic model to achieve accurate trajectory tracking and smooth mode transition. We validate our framework through extensive benchmark comparisons and experiments, demonstrating its effectiveness in terms of planning quality and control performance.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (29)
  1. A. Kalantari and M. Spenko, “Design and experimental validation of hytaq, a hybrid terrestrial and aerial quadrotor,” in 2013 IEEE International Conference on Robotics and Automation.   IEEE, 2013, pp. 4445–4450.
  2. C. J. Dudley, A. C. Woods, and K. K. Leang, “A micro spherical rolling and flying robot,” in 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE, 2015, pp. 5863–5869.
  3. S. Morton and N. Papanikolopoulos, “A small hybrid ground-air vehicle concept,” in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE, 2017, pp. 5149–5154.
  4. S. Mintchev and D. Floreano, “A multi-modal hovering and terrestrial robot with adaptive morphology,” in Proceedings of the 2nd International Symposium on Aerial Robotics, no. CONF, 2018.
  5. S. Sabet, A.-A. Agha-Mohammadi, A. Tagliabue, D. S. Elliott, and P. E. Nikravesh, “Rollocopter: An energy-aware hybrid aerial-ground mobility for extreme terrains,” in 2019 IEEE Aerospace Conference.   IEEE, 2019, pp. 1–8.
  6. B. Li, L. Ma, D. Wang, and Y. Sun, “Driving and tilt-hovering–an agile and manoeuvrable aerial vehicle with tiltable rotors,” IET Cyber-Systems and Robotics, 2021.
  7. H. C. Choi, I. Wee, M. Corah, S. Sabet, T. Kim, T. Touma, D. H. Shim, and A.-a. Agha-mohammadi, “Baxter: Bi-modal aerial-terrestrial hybrid vehicle for long-endurance versatile mobility: Preprint version,” arXiv preprint arXiv:2102.02942, 2021.
  8. N. B. David and D. Zarrouk, “Design and analysis of fcstar, a hybrid flying and climbing sprawl tuned robot,” IEEE Robotics and Automation Letters, 2021.
  9. K. Kim, P. Spieler, E.-S. Lupu, A. Ramezani, and S.-J. Chung, “A bipedal walking robot that can fly, slackline, and skateboard,” Science Robotics, vol. 6, no. 59, p. eabf8136, 2021.
  10. H. Jia, S. Bai, R. Ding, J. Shu, Y. Deng, B. L. Khoo, and P. Chirarattananon, “A quadrotor with a passively reconfigurable airframe for hybrid terrestrial locomotion,” IEEE/ASME Transactions on Mechatronics, vol. 27, no. 6, pp. 4741–4751, 2022.
  11. B. Araki, J. Strang, S. Pohorecky, C. Qiu, T. Naegeli, and D. Rus, “Multi-robot path planning for a swarm of robots that can both fly and drive,” in 2017 IEEE International Conference on Robotics and Automation (ICRA).   IEEE, 2017, pp. 5575–5582.
  12. A. Sharif, H. Lahiru, S. Herath, and H. Roth, “Energy efficient path planning of hybrid fly-drive robot (hyfdr) using a* algorithm.” in ICINCO (2), 2018, pp. 211–220.
  13. S. Choudhury, J. P. Knickerbocker, and M. J. Kochenderfer, “Dynamic real-time multimodal routing with hierarchical hybrid planning,” in 2019 IEEE Intelligent Vehicles Symposium (IV).   IEEE, 2019, pp. 2397–2404.
  14. D. D. Fan, R. Thakker, T. Bartlett, M. B. Miled, L. Kim, E. Theodorou, and A.-a. Agha-mohammadi, “Autonomous hybrid ground/aerial mobility in unknown environments,” in 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE, 2019, pp. 3070–3077.
  15. R. Zhang, Y. Wu, L. Zhang, C. Xu, and F. Gao, “Autonomous and adaptive navigation for terrestrial-aerial bimodal vehicles,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 3008–3015, 2022.
  16. T. Wu, Y. Zhu, L. Zhang, J. Yang, and Y. Ding, “Unified terrestrial/aerial motion planning for hytaqs via nmpc,” IEEE Robotics and Automation Letters, 2023.
  17. J. Colmenares-Vázquez, P. Castillo, N. Marchand, and D. Huerta-García, “Nonlinear control for ground-air trajectory tracking by a hybrid vehicle: theory and experiments,” IFAC-PapersOnLine, vol. 52, no. 8, pp. 19–24, 2019.
  18. J. Yang, Y. Zhu, L. Zhang, Y. Dong, and Y. Ding, “Sytab: A class of smooth-transition hybrid terrestrial/aerial bicopters,” IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 9199–9206, 2022.
  19. S. Sun, A. Romero, P. Foehn, E. Kaufmann, and D. Scaramuzza, “A comparative study of nonlinear mpc and differential-flatness-based control for quadrotor agile flight,” IEEE Transactions on Robotics, vol. 38, no. 6, pp. 3357–3373, 2022.
  20. S. Atay, M. Bryant, and G. Buckner, “Control and control allocation for bimodal, rotary wing, rolling–flying vehicles,” Journal of Mechanisms and Robotics, vol. 13, 2021.
  21. F. Nan, S. Sun, P. Foehn, and D. Scaramuzza, “Nonlinear mpc for quadrotor fault-tolerant control,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 5047–5054, 2022.
  22. D. Mellinger and V. Kumar, “Minimum snap trajectory generation and control for quadrotors,” in Proc. of the IEEE Intl. Conf. on Robot. and Autom. (ICRA), Shanghai, China, May 2011, pp. 2520–2525.
  23. M. Faessler, A. Franchi, and D. Scaramuzza, “Differential flatness of quadrotor dynamics subject to rotor drag for accurate tracking of high-speed trajectories,” IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 620–626, 2017.
  24. M. Watterson and V. Kumar, “Control of quadrotors using the hopf fibration on so (3),” in Robotics Research: The 18th International Symposium ISRR.   Springer, 2019, pp. 199–215.
  25. Z. Wang, C. Xu, and F. Gao, “Robust trajectory planning for spatial-temporal multi-drone coordination in large scenes,” in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   IEEE, 2022, pp. 12 182–12 188.
  26. D. Dolgov, S. Thrun, M. Montemerlo, and J. Diebel, “Practical search techniques in path planning for autonomous driving,” Ann Arbor, vol. 1001, no. 48105, pp. 18–80, 2008.
  27. Z. Wang, X. Zhou, C. Xu, and F. Gao, “Geometrically constrained trajectory optimization for multicopters,” IEEE Transactions on Robotics, vol. 38, no. 5, pp. 3259–3278, 2022.
  28. B. Houska, H. J. Ferreau, and M. Diehl, “Acado toolkit—an open-source framework for automatic control and dynamic optimization,” Optimal Control Applications and Methods, vol. 32, no. 3, pp. 298–312, 2011.
  29. H. J. Ferreau, C. Kirches, A. Potschka, H. G. Bock, and M. Diehl, “qpoases: A parametric active-set algorithm for quadratic programming,” Mathematical Programming Computation, vol. 6, pp. 327–363, 2014.
Citations (5)

Summary

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