A Smoothing Algorithm for Minimum Sensing Path Plans in Gaussian Belief Space.
Ali Reza PedramTakashi TanakaPublished in: CoRR (2023)
Keyphrases
- belief space
- smoothing algorithm
- planning under uncertainty
- state space
- edge preserving
- motion planning
- dynamic environments
- initial state
- belief state
- image flow
- velocity field
- action sequences
- degrees of freedom
- markov random field
- partially observable
- planning graph
- ai planning
- maximum likelihood
- decision theoretic
- path planning
- partially observable markov decision processes
- classical planning
- planning process
- reinforcement learning
- computer vision
- random fields
- signal to noise ratio
- dynamical systems
- heuristic search
- planning problems
- mobile robot
- multi agent
- image restoration