From Kinematics to Dynamics: Learning to Refine Hybrid Plans for Physically Feasible Execution
In many robotic tasks, agents must traverse a sequence of spatial regions to complete a mission. Such problems are inherently mixed discrete-continuous: a high-level action sequence and a physically feasible continuous trajectory. The resulting trajectory and action sequence must also satisfy problem constraints such as deadlines, time windows, and velocity or acceleration limits. While hybrid temporal planners attempt to address this challenge, they typically model motion using linear (first-order) dynamics, which cannot guarantee that the resulting plan respects the robot's true physical constraints. Consequently, even when the high-level action sequence is fixed, producing a dynamicall...
| Authors | Lidor Erez, Shahaf S. Shperberg, Ayal Taitler |
|---|---|
| Primary category | cs.RO |
| Published | 14 April 2026 |
| Last updated at source | 4 June 2026 |
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