Toward Generalist Neural Motion Planners for Robotic Manipulators: Challenges and Opportunities
State-of-the-art generalist manipulation policies have enabled the deployment of robotic manipulators in unstructured human environments. However, these frameworks struggle in cluttered environments primarily because they utilize auxiliary modules for low-level motion planning and control. Motion planning remains challenging due to the high dimensionality of the robot's configuration space and the presence of workspace obstacles. Neural motion planners have enhanced motion planning efficiency by offering fast inference and effectively handling the inherent multi-modality of the motion planning problem. Despite such benefits, current neural motion planners often struggle to generalize to u...
| Authors | Davood Soleymanzadeh, Ivan Lopez-Sanchez, Hao Su et al. |
|---|---|
| Primary category | cs.RO |
| Published | 25 March 2026 |
| Last updated at source | 25 March 2026 |
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