Speeding up Gaussian Belief Space Planning for Underwater Robots Through a Covariance Upper Bound
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2933067
Abstract: Existing belief space motion planning methods are not efficient for underwater robots that are subject to spatially varying motion and sensing uncertainties arising from the non-uniform current disturbances and landmark populations, respectively. Based on a… read more here.
Keywords: belief; gaussian belief; covariance; belief space ... See more keywords
Uncertainty-Constrained Differential Dynamic Programming in Belief Space for Vision Based Robots
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2021.3062338
Abstract: Most mobile robots follow a modular sense-plan-act system architecture that can lead to poor performance or even catastrophic failure for visual inertial navigation systems due to trajectories devoid of feature matches. Planning in belief space… read more here.
Keywords: differential dynamic; uncertainty; belief space; dynamic programming ... See more keywords
FT-BSP: Focused Topological Belief Space Planning
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2021.3068947
Abstract: At its core, decision making under uncertainty can be regarded as sorting candidate actions according to a certain objective. While finding the optimal solution directly is computationally expensive, other approaches that produce the same ordering… read more here.
Keywords: belief space; optimal solution; space planning; candidate actions ... See more keywords
Path-Tree Optimization in Discrete Partially Observable Environments Using Rapidly-Exploring Belief-Space Graphs
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3191944
Abstract: Robots often need to solve path planning problems where essential and discrete aspects of the environment are partially observable. This introduces a multi-modality, where the robot must be able to observe and infer the state… read more here.
Keywords: belief space; space; path tree;
Asymptotic Optimality of Finite Model Approximations for Partially Observed Markov Decision Processes With Discounted Cost
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2019.2907172
Abstract: We consider finite model approximations of discrete-time partially observed Markov decision processes (POMDPs) under the discounted cost criterion. After converting the original partially observed stochastic control problem to a fully observed one on the belief… read more here.
Keywords: markov decision; model; partially observed; belief space ... See more keywords