Biomechanics-Aware Trajectory Optimization for Online Navigation during Robotic Physiotherapy
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866909684766605312 |
|---|---|
| author | Belli, Italo van Melis, Florian Prendergast, J. Micah Seth, Ajay Peternel, Luka |
| author_facet | Belli, Italo van Melis, Florian Prendergast, J. Micah Seth, Ajay Peternel, Luka |
| contents | Robotic devices provide a great opportunity to assist in delivering physical therapy and rehabilitation movements, yet current robot-assisted methods struggle to incorporate biomechanical metrics essential for safe and effective therapy. We introduce BATON, a Biomechanics-Aware Trajectory Optimization approach to online robotic Navigation of human musculoskeletal loads for rotator cuff rehabilitation. BATON embeds a high-fidelity OpenSim model of the human shoulder into an optimal control framework, generating strain-minimizing trajectories for real-time control of therapeutic movements. \addedText{Its core strength lies in the ability to adapt biomechanics-informed trajectories online to unpredictable volitional human actions or reflexive reactions during physical human-robot interaction based on robot-sensed motion and forces. BATON's adaptability is enabled by a real-time, model-based estimator that infers changes in muscle activity via a rapid redundancy solver driven by robot pose and force/torque sensor data. We validated BATON through physical human-robot interaction experiments, assessing response speed, motion smoothness, and interaction forces. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_03873 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Biomechanics-Aware Trajectory Optimization for Online Navigation during Robotic Physiotherapy Belli, Italo van Melis, Florian Prendergast, J. Micah Seth, Ajay Peternel, Luka Robotics Systems and Control Robotic devices provide a great opportunity to assist in delivering physical therapy and rehabilitation movements, yet current robot-assisted methods struggle to incorporate biomechanical metrics essential for safe and effective therapy. We introduce BATON, a Biomechanics-Aware Trajectory Optimization approach to online robotic Navigation of human musculoskeletal loads for rotator cuff rehabilitation. BATON embeds a high-fidelity OpenSim model of the human shoulder into an optimal control framework, generating strain-minimizing trajectories for real-time control of therapeutic movements. \addedText{Its core strength lies in the ability to adapt biomechanics-informed trajectories online to unpredictable volitional human actions or reflexive reactions during physical human-robot interaction based on robot-sensed motion and forces. BATON's adaptability is enabled by a real-time, model-based estimator that infers changes in muscle activity via a rapid redundancy solver driven by robot pose and force/torque sensor data. We validated BATON through physical human-robot interaction experiments, assessing response speed, motion smoothness, and interaction forces. |
| title | Biomechanics-Aware Trajectory Optimization for Online Navigation during Robotic Physiotherapy |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2411.03873 |