Bi-Level Optimization for Contact and Motion Planning in Rope-Assisted Legged Robots
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866911633315463168 |
|---|---|
| author | Malacarne, Ruben Tsikelis, Ioannis Hoffman, Enrico Mingo Focchi, Michele |
| author_facet | Malacarne, Ruben Tsikelis, Ioannis Hoffman, Enrico Mingo Focchi, Michele |
| contents | This paper presents a planning pipeline framework for locomotion in rope-assisted robots climbing vertical surfaces. The proposed framework is formulated as a bi-level optimization scheme that addresses a mixed-integer problem: selecting feasible terrain regions for landing while simultaneously optimizing the control inputs, namely rope tensions and leg forces, and landing location. The outer level of the optimization is solved using the Cross-Entropy Method, while the inner level relies on gradient-based nonlinear optimization to compute dynamically feasible motions. The approach is validated on a novel climbing robot platform, ALPINE, across a variety of challenging terrain configurations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_26910 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Bi-Level Optimization for Contact and Motion Planning in Rope-Assisted Legged Robots Malacarne, Ruben Tsikelis, Ioannis Hoffman, Enrico Mingo Focchi, Michele Robotics This paper presents a planning pipeline framework for locomotion in rope-assisted robots climbing vertical surfaces. The proposed framework is formulated as a bi-level optimization scheme that addresses a mixed-integer problem: selecting feasible terrain regions for landing while simultaneously optimizing the control inputs, namely rope tensions and leg forces, and landing location. The outer level of the optimization is solved using the Cross-Entropy Method, while the inner level relies on gradient-based nonlinear optimization to compute dynamically feasible motions. The approach is validated on a novel climbing robot platform, ALPINE, across a variety of challenging terrain configurations. |
| title | Bi-Level Optimization for Contact and Motion Planning in Rope-Assisted Legged Robots |
| topic | Robotics |
| url | https://arxiv.org/abs/2604.26910 |