NTFields: Neural Time Fields for Physics-Informed Robot Motion Planning. (arXiv:2210.00120v1 [cs.RO] CROSS LISTED)

Neural Motion Planners (NMPs) have emerged as a promising tool for solving
robot navigation tasks in complex environments. However, these methods often
require expert data for learning, which limits their application to scenarios
where data generation is time-consuming. Recent developments have also led to
physics-informed deep neural models capable of representing complex dynamical
Partial Differential Equations (PDEs). Inspired by these developments, we
propose Neural Time Fields (NTFields) for robot motion planning in cluttered
scenarios. Our framework represents a wave propagation …

arxiv motion planning physics planning robot