Perceptive Locomotion through Whole-Body MPC and Optimal Region Selection
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
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2023
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| _version_ | 1866913224022032384 |
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| author | Corbères, Thomas Mastalli, Carlos Merkt, Wolfgang Havoutis, Ioannis Fallon, Maurice Mansard, Nicolas Flayols, Thomas Vijayakumar, Sethu Tonneau, Steve |
| author_facet | Corbères, Thomas Mastalli, Carlos Merkt, Wolfgang Havoutis, Ioannis Fallon, Maurice Mansard, Nicolas Flayols, Thomas Vijayakumar, Sethu Tonneau, Steve |
| contents | Real-time synthesis of legged locomotion maneuvers in challenging industrial settings is still an open problem, requiring simultaneous determination of footsteps locations several steps ahead while generating whole-body motions close to the robot's limits. State estimation and perception errors impose the practical constraint of fast re-planning motions in a model predictive control (MPC) framework. We first observe that the computational limitation of perceptive locomotion pipelines lies in the combinatorics of contact surface selection. Re-planning contact locations on selected surfaces can be accomplished at MPC frequencies (50-100 Hz). Then, whole-body motion generation typically follows a reference trajectory for the robot base to facilitate convergence. We propose removing this constraint to robustly address unforeseen events such as contact slipping, by leveraging a state-of-the-art whole-body MPC (Croccodyl). Our contributions are integrated into a complete framework for perceptive locomotion, validated under diverse terrain conditions, and demonstrated in challenging trials that push the robot's actuation limits, as well as in the ICRA 2023 quadruped challenge simulation. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2305_08926 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Perceptive Locomotion through Whole-Body MPC and Optimal Region Selection Corbères, Thomas Mastalli, Carlos Merkt, Wolfgang Havoutis, Ioannis Fallon, Maurice Mansard, Nicolas Flayols, Thomas Vijayakumar, Sethu Tonneau, Steve Robotics Real-time synthesis of legged locomotion maneuvers in challenging industrial settings is still an open problem, requiring simultaneous determination of footsteps locations several steps ahead while generating whole-body motions close to the robot's limits. State estimation and perception errors impose the practical constraint of fast re-planning motions in a model predictive control (MPC) framework. We first observe that the computational limitation of perceptive locomotion pipelines lies in the combinatorics of contact surface selection. Re-planning contact locations on selected surfaces can be accomplished at MPC frequencies (50-100 Hz). Then, whole-body motion generation typically follows a reference trajectory for the robot base to facilitate convergence. We propose removing this constraint to robustly address unforeseen events such as contact slipping, by leveraging a state-of-the-art whole-body MPC (Croccodyl). Our contributions are integrated into a complete framework for perceptive locomotion, validated under diverse terrain conditions, and demonstrated in challenging trials that push the robot's actuation limits, as well as in the ICRA 2023 quadruped challenge simulation. |
| title | Perceptive Locomotion through Whole-Body MPC and Optimal Region Selection |
| topic | Robotics |
| url | https://arxiv.org/abs/2305.08926 |