Home Knowledge Base Kinematics to Dynamics: Learning to Refine Hybrid Plans for Physically Feasible

Kinematics to Dynamics: Learning to Refine Hybrid Plans for Physically Feasible

No mentions found

This entity hasn't been tracked yet, or Iris is still building its knowledge base.

Related Articles from SNS

From Kinematics to Dynamics: Learning to Refine Hybrid Plans for Physically Feasible Execution

arXiv:2604.12474v3 Announce Type: replace Abstract: 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.

arXiv CS 5d ago