Sandwich Approach for Motion Planning and Control (2309.16874v2)
Abstract: This paper develops a new approach for robot motion planning and control in obstacle-laden environments that is inspired by fundamentals of fluid mechanics. For motion planning, we propose a novel transformation between motion space, with arbitrary obstacles of random sizes and shapes, and an obstacle-free planning space with geodesically-varying distances and constrained transitions. We then obtain robot desired trajectory by A* searching over a uniform grid distributed over the planning space. We show that implementing the A* search over the planning space can generate shorter paths when compared to the existing A* searching over the motion space. For trajectory tracking, we propose an MPC-based trajectory tracking control, with linear equality and inequality safety constraints, enforcing the safety requirements of planning and control.
- A. D. Ames, S. Coogan, M. Egerstedt, G. Notomista, K. Sreenath, and P. Tabuada, “Control barrier functions: Theory and applications,” in 2019 18th European Control Conference (ECC), 2019, pp. 3420–3431.
- F. Ferraguti, C. T. Landi, A. Singletary, H.-C. Lin, A. Ames, C. Secchi, and M. Bonfè, “Safety and efficiency in robotics: The control barrier functions approach,” IEEE Robotics & Automation Magazine, vol. 29, no. 3, pp. 139–151, 2022.
- J. Breeden and D. Panagou, “High relative degree control barrier functions under input constraints,” in 2021 60th IEEE Conference on Decision and Control (CDC). IEEE, 2021, pp. 6119–6124.
- R. Cheng, G. Orosz, R. M. Murray, and J. W. Burdick, “End-to-end safe reinforcement learning through barrier functions for safety-critical continuous control tasks,” in Proceedings of the AAAI conference on artificial intelligence, vol. 33, no. 01, 2019, pp. 3387–3395.
- J. Zeng, B. Zhang, and K. Sreenath, “Safety-critical model predictive control with discrete-time control barrier function,” in 2021 American Control Conference (ACC), 2021, pp. 3882–3889.
- R. Grandia, F. Farshidian, R. Ranftl, and M. Hutter, “Feedback mpc for torque-controlled legged robots,” in 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019, pp. 4730–4737.
- Z. Marvi and B. Kiumarsi, “Safety planning using control barrier function: A model predictive control scheme,” in 2019 IEEE 2nd Connected and Automated Vehicles Symposium (CAVS). IEEE, 2019, pp. 1–5.
- V. Varun, A. P. Vinod, and S. Kolathaya, “Motion planning with dynamic obstacles using convexified control barrier functions,” in 2021 Seventh Indian Control Conference (ICC). IEEE, 2021, pp. 81–86.
- D. G. Crowdy, “Analytical solutions for uniform potential flow past multiple cylinders,” European Journal of Mechanics-B/Fluids, vol. 25, no. 4, pp. 459–470, 2006.
- ——, “Uniform flow past a periodic array of cylinders,” European Journal of Mechanics-B/Fluids, vol. 56, pp. 120–129, 2016.
- H. Rastgoftar and E. Atkins, “Physics-based freely scalable continuum deformation for uas traffic coordination,” IEEE Transactions on Control of Network Systems, vol. 7, no. 2, pp. 532–544, 2019.
- A. E. Asslouj, E. Atkins, and H. Rastgoftar, “Can a laplace pde define air corridors through low-altitude airspace?” in 2023 International Conference on Unmanned Aircraft Systems (ICUAS), 2023, pp. 1–8.
- H. Rastgoftar and I. V. Kolmanovsky, “Safe affine transformation-based guidance of a large-scale multiquadcopter system,” IEEE Transactions on Control of Network Systems, vol. 8, no. 2, pp. 640–653, 2021.
- A. El Asslouj and H. Rastgoftar, “Quadcopter tracking using euler-angle-free flatness-based control,” in 2023 European Control Conference (ECC). IEEE, 2023, pp. 1–6.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
