Tonneau, Steve

Flayols, Thomas

Corbères, Thomas

2025-02-19T11:20:36Z

2025-02-19T11:20:36Z

2025-02-19

Real-time synthesis of legged locomotion manoeuvres in challenging environments, such as industrial staircases with distinct contact surfaces, remains an unresolved problem. These environments, known as multi-contact environments, require the simultaneous determination of footstep locations several steps ahead while generating whole-body motions close to the robot's operational limits. The practical constraint of state estimation and perception errors necessitates rapid re-planning of motions. With traditional model-based methods, this constraint prevents using a single large optimisation to solve the entire locomotion problem, leading to problem decomposition into smaller, more manageable sub-problems to meet computing time requirements. However, such decomposition introduces issues such as loose coupling between sub-problems due to varying models, constraints, and horizons, highlighting the need for an efficient architecture. Decomposition, particularly at the contact level to manage complexity, exacerbates the challenge of addressing combinatorial problems in multi-contact environments. We propose a fully decomposed control architecture to address the locomotion problem, leveraging mixed-integer optimisation with conservative assumptions as a planner to select only the contact surfaces while continuously updating footstep positions and leg trajectories within these surfaces. The approach was initially validated on the quadruped robot Solo and later extended to include real-time perception with the larger industrial robot ANYmal-B. Additionally, we explore integrating learning-based methods along with trajectory optimisation frameworks to leverage the strengths of both approaches and enhance the planner's performance.

https://hdl.handle.net/1842/43123

http://dx.doi.org/10.7488/era/5666

en

The University of Edinburgh

Thomas Corbères, Thomas Flayols, Pierre-Alexandre Léziart, Rohan Budhiraja, Philippe Souères, Guilhem Saurel, and Nicolas Mansard. "Comparison of predictive controllers for locomotion and balance recovery of quadruped robots". In 2021 IEEE International Conference on Robotics and Automation (ICRA), pages. 5021-5027, 2021.

Fanny Risbourg∗ , Thomas Corbères∗ , Pierre-Alexandre Léziart, Thomas Flayols, Nicolas Mansard, and Steve Tonneau. "Real-time footstep planning and control of the solo quadruped robot in 3d environments". In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 12950-12956, 2022.

Pierre-Alexandre Léziart, Thomas Corbères, Thomas Flayols, Steve Tonneau, Nicolas Mansard, and Philippe Souères. "Improved control scheme for the solo quadruped and experimental comparison of model predictive controllers". IEEE Robotics and Automation Letters (RA-L), 7(4):9945-9952, 2022.

Carlos Mastalli, Saroj Prasad Chhatoi, Thomas Corbères, Steve Tonneau, and Sethu Vijayakumar. "Inverse-dynamics mpc via nullspace resolution". IEEE Transactions on Robotics (TRO), 39(4):3222-3241, 2023

Jaehyun Shim, Carlos Mastalli, Thomas Corbères, Steve Tonneau, Vladimir Ivan, and Sethu Vijayakumar. Topology-based mpc for automatic footstep placement and contact surface selection. In 2023 IEEE International Conference on Robotics and Automation (ICRA), pages 12226-12232, 2023

Gianni Lunardi, Thomas Corbères, Carlos Mastalli, Nicolas Mansard, Thomas Flayols, Steve Tonneau, and Andrea Del Prete. Reference- free model predictive control for quadrupedal locomotion. IEEE Access, 12:689-698, 2024

Corbères, T., Mastalli, C., Merkt, W., Havoutis, I., Fallon, M., Mansard, N., Flayols, T., Vijayakumar, S. and Tonneau, S. (2024), ‘Perceptive locomotion through whole-body mpc and optimal region selection’. URL: https://arxiv.org/abs/2305.08926

multi-contact environments

footstep locations

robot’s operational limits

whole-body motions

traditional model-based methods

decomposition

decomposed control architecture

mixed-integer optimisation

quadruped robots

trajectory optimisation framework

Complete framework for agile quadruped locomotion: integrating real-time control, planning, and perception in multi-contact environments

A complete framework for agile quadruped locomotion: integrating real-time control, planning, and perception in multi-contact environments

Thesis or Dissertation

Doctoral

PhD Doctor of Philosophy