NAS: N-step computation of All Solutions to the footstep planning problem
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866914969852837888 |
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| author | Wang, Jiayi Samadi, Saeid Wang, Hefan Fernbach, Pierre Stasse, Olivier Vijayakumar, Sethu Tonneau, Steve |
| author_facet | Wang, Jiayi Samadi, Saeid Wang, Hefan Fernbach, Pierre Stasse, Olivier Vijayakumar, Sethu Tonneau, Steve |
| contents | How many ways are there to climb a staircase in a given number of steps? Infinitely many, if we focus on the continuous aspect of the problem. A finite, possibly large number if we consider the discrete aspect, \emph{i.e.} on which surface which effectors are going to step and in what order. We introduce NAS, an algorithm that considers both aspects simultaneously and computes \emph{all} the possible solutions to such a contact planning problem, under standard assumptions. To our knowledge NAS is the first algorithm to produce a globally optimal policy, efficiently queried in real time for planning the next footsteps of a humanoid robot.
Our empirical results (in simulation and on the Talos platform) demonstrate that, despite the theoretical exponential complexity, optimisations reduce the practical complexity of NAS to a manageable bilinear form, maintaining completeness guarantees and enabling efficient GPU parallelisation. NAS is demonstrated in a variety of scenarios for the Talos robot, both in simulation and on the hardware platform. Future work will focus on further reducing computation times and extending the algorithm's applicability beyond gaited locomotion. Our video is available at \url{https://youtu.be/I5yFe0ez0sI} |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_12962 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | NAS: N-step computation of All Solutions to the footstep planning problem Wang, Jiayi Samadi, Saeid Wang, Hefan Fernbach, Pierre Stasse, Olivier Vijayakumar, Sethu Tonneau, Steve Robotics How many ways are there to climb a staircase in a given number of steps? Infinitely many, if we focus on the continuous aspect of the problem. A finite, possibly large number if we consider the discrete aspect, \emph{i.e.} on which surface which effectors are going to step and in what order. We introduce NAS, an algorithm that considers both aspects simultaneously and computes \emph{all} the possible solutions to such a contact planning problem, under standard assumptions. To our knowledge NAS is the first algorithm to produce a globally optimal policy, efficiently queried in real time for planning the next footsteps of a humanoid robot. Our empirical results (in simulation and on the Talos platform) demonstrate that, despite the theoretical exponential complexity, optimisations reduce the practical complexity of NAS to a manageable bilinear form, maintaining completeness guarantees and enabling efficient GPU parallelisation. NAS is demonstrated in a variety of scenarios for the Talos robot, both in simulation and on the hardware platform. Future work will focus on further reducing computation times and extending the algorithm's applicability beyond gaited locomotion. Our video is available at \url{https://youtu.be/I5yFe0ez0sI} |
| title | NAS: N-step computation of All Solutions to the footstep planning problem |
| topic | Robotics |
| url | https://arxiv.org/abs/2407.12962 |