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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2209.15566 |
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| _version_ | 1866916374127837184 |
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| author | Bratta, Angelo Meduri, Avadesh Focchi, Michele Righetti, Ludovic Semini, Claudio |
| author_facet | Bratta, Angelo Meduri, Avadesh Focchi, Michele Righetti, Ludovic Semini, Claudio |
| contents | In legged logomotion, online trajectory optimization techniques generally depend on heuristic-based contact planners in order to have low computation times and achieve high replanning frequencies. In this work, we propose ContactNet, a fast acyclic contact planner based on a multi-output regression neural network. ContactNet ranks discretized stepping regions, allowing to quickly choose the best feasible solution, even in complex environments. The low computation time, in the order of 1 ms, makes possible the execution of the contact planner concurrently with a trajectory optimizer in a Model Predictive Control (MPC) fashion. We demonstrate the effectiveness of the approach in simulation in different complex scenarios with the quadruped robot Solo12. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2209_15566 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | ContactNet: Online Multi-Contact Planning for Acyclic Legged Robot Locomotion Bratta, Angelo Meduri, Avadesh Focchi, Michele Righetti, Ludovic Semini, Claudio Robotics In legged logomotion, online trajectory optimization techniques generally depend on heuristic-based contact planners in order to have low computation times and achieve high replanning frequencies. In this work, we propose ContactNet, a fast acyclic contact planner based on a multi-output regression neural network. ContactNet ranks discretized stepping regions, allowing to quickly choose the best feasible solution, even in complex environments. The low computation time, in the order of 1 ms, makes possible the execution of the contact planner concurrently with a trajectory optimizer in a Model Predictive Control (MPC) fashion. We demonstrate the effectiveness of the approach in simulation in different complex scenarios with the quadruped robot Solo12. |
| title | ContactNet: Online Multi-Contact Planning for Acyclic Legged Robot Locomotion |
| topic | Robotics |
| url | https://arxiv.org/abs/2209.15566 |