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Belief space planning assuming maximum likelihood observations
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-642-14743-2_25openalex-snapshot
The Belief Roadmap: Efficient Planning in Linear POMDPs by Factoring the Covariance
inferredcites →https://doi.org/10.1016/b978-1-55860-377-6.50052-9openalex-snapshot
Learning policies for partially observable environments: Scaling up
inferredcites →https://doi.org/10.1109/acc.2009.5159963openalex-snapshot
Coordinated guidance of autonomous uavs via nominal belief-state optimization
inferredcites →https://doi.org/10.1109/robot.2006.1641793openalex-snapshot
Bayesian estimation for autonomous object manipulation based on tactile sensors
inferredcites →https://doi.org/10.1115/1.1483351openalex-snapshot
Practical Methods for Optimal Control using Nonlinear Programming
inferredcites →https://doi.org/10.1177/02783640122067453openalex-snapshot
Randomized Kinodynamic Planning
inferredcites →https://doi.org/10.1177/0278364911406562openalex-snapshot
LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information
inferredcites →https://doi.org/10.1287/moor.12.3.441openalex-snapshot
The Complexity of Markov Decision Processes
inferredcites →https://doi.org/10.15607/rss.2009.v.003openalex-snapshot
LQR-trees: Feedback motion planning on sparse randomized trees
inferredcites →https://doi.org/10.15607/rss.2010.vi.017openalex-snapshot
LQG-MP: Optimized Path Planning for Robots with Motion Uncertainty and Imperfect State Information
inferredcites →https://doi.org/10.1613/jair.678openalex-snapshot
Value-Function Approximations for Partially Observable Markov Decision Processes
inferredcites →https://doi.org/10.48550/arxiv.1203.3477openalex-snapshot
A Scalable Method for Solving High-Dimensional Continuous POMDPs Using Local Approximation
inferredcites →https://doi.org/10.7551/mitpress/8727.003.0004openalex-snapshot
LQR-Trees: Feedback Motion Planning on Sparse Randomized Trees
inferredcites →https://doi.org/10.7551/mitpress/9123.003.0021openalex-snapshot
LQG-MP: Optimized Path Planning for Robots with Motion Uncertainty and Imperfect State Information
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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An Online POMDP Solver for Uncertainty Planning in Dynamic Environment
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Safe Motion Planning for Imprecise Robotic Manipulators by Minimizing Probability of Collision
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Pre-image Backchaining in Belief Space for Mobile Manipulation
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Motion Planning Under Uncertainty Using Differential Dynamic Programming in Belief Space
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Design, Sensing, and Planning: Fundamentally Coupled Problems for Continuum Robots
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Randomized Belief-Space Replanning in Partially-Observable Continuous Spaces
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Convex Receding Horizon Control in Non-Gaussian Belief Space
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Decentralized multi-robot belief space planning in unknown environments via identification and efficient re-evaluation of impacted paths
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Bayesian incremental inference update by re-using calculations from belief space planning: a new paradigm
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Multimodal embodied attribute learning by robots for object-centric action policies
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Risk-Aware Path Planning Under Uncertainty in Dynamic Environments
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An Integrated Localization, Motion Planning and Obstacle Avoidance Algorithm in Belief Space
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Reasoning about uncertain parameters and agent behaviors through encoded experiences and belief planning
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Finite-horizon LQR controller for partially-observed Boolean dynamical systems
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Speeding up Gaussian Belief Space Planning for Underwater Robots Through a Covariance Upper Bound
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Actively Learning Gaussian Process Dynamical Systems Through Global and Local Explorations
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Model Identification Adaptive Control with ρ-POMDP Planning
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Formalizing human-robot mutual adaptation: A bounded memory model
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Manipulation planning using model-based belief dynamics
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Path planning in belief space with pose SLAM
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Closed-loop belief space planning for linear, Gaussian systems
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Rapidly-exploring Random Belief Trees for motion planning under uncertainty
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LQG-obstacles: Feedback control with collision avoidance for mobile robots with motion and sensing uncertainty
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Estimating probability of collision for safe motion planning under Gaussian motion and sensing uncertainty
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LQR-RRT*: Optimal sampling-based motion planning with automatically derived extension heuristics
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Motion planning for paramagnetic microparticles under motion and sensing uncertainty
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Online parameter estimation via real-time replanning of continuous Gaussian POMDPs
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An online and approximate solver for POMDPs with continuous action space
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Active exploration using trajectory optimization for robotic grasping in the presence of occlusions
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Feedback motion planning under non-Gaussian uncertainty and non-convex state constraints
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Implicit belief-space pre-images for hierarchical planning and execution
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T-LQG: Closed-loop belief space planning via trajectory-optimized LQG
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Consistent sparsification for efficient decision making under uncertainty in high dimensional state spaces
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Towards efficient inference update through planning via JIP — Joint inference and belief space planning
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MT-LQG: Multi-agent planning in belief space via trajectory-optimized LQG
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No-regret replanning under uncertainty
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Integration of Local Geometry and Metric Information in Sampling-Based Motion Planning
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Topological Multi-Robot Belief Space Planning in Unknown Environments
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Robust, Compliant Assembly via Optimal Belief Space Planning
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Reliably Arranging Objects in Uncertain Domains
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Vision Based Collaborative Path Planning for Micro Aerial Vehicles
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Belief Space Planning for Reducing Terrain Relative Localization Uncertainty in Noisy Elevation Maps
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iX-BSP: Belief Space Planning through Incremental Expectation
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Online adaptation of uncertain models using neural network priors and partially observable planning
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Uncertainty-Aware Path Planning for Navigation on Road Networks Using Augmented MDPs
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A Unified Closed-Loop Motion Planning Approach For An I-AUV In Cluttered Environment With Localization Uncertainty
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Online Replanning in Belief Space for Partially Observable Task and Motion Problems
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Generating Visibility-Aware Trajectories for Cooperative and Proactive Motion Planning
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Adaptive Authority Allocation in Shared Control of Robots Using Bayesian Filters
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Act, Perceive, and Plan in Belief Space for Robot Localization
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Fully Persistent Spatial Data Structures for Efficient Queries in Path-Dependent Motion Planning Applications
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Risk-aware Spatio-temporal Logic Planning in Gaussian Belief Spaces
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Focused Adaptation of Dynamics Models for Deformable Object Manipulation
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Decision diagrams as plans: Answering observation-grounded queries
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Probabilistic Active Loop Closure for Autonomous Exploration
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IBBT: Informed Batch Belief Trees for Motion Planning Under Uncertainty
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Knowledge acquisition plans: Generation, combination, and execution
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Constrained Hierarchical Monte Carlo Belief-State Planning
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FIRM: Feedback controller-based information-state roadmap - A framework for motion planning under uncertainty
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A hierarchical method for stochastic motion planning in uncertain environments
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Foresight and reconsideration in hierarchical planning and execution
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Sigma hulls for Gaussian belief space planning for imprecise articulated robots amid obstacles
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Uncertainty-driven survey path planning for bathymetric mapping
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Dual execution of optimized contact interaction trajectories
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Motion planning under uncertainty for medical needle steering using optimization in belief space
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Health aware stochastic planning for persistent package delivery missions using quadrotors
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POMDP manipulation via trajectory optimization
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Risk aversion in belief-space planning under measurement acquisition uncertainty
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Belief space planning for underwater cooperative localization
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Heuristic search in belief space for motion planning under uncertainties
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Towards multi-robot active collaborative state estimation via belief space planning
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Modular task and motion planning in belief space
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Computationally efficient decision making under uncertainty in high-dimensional state spaces
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Occlusion-aware multi-robot 3D tracking
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Multi-robot decentralized belief space planning in unknown environments via efficient re-evaluation of impacted paths
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Interleaving motion in contact and in free space for planning under uncertainty
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Scalable sparsification for efficient decision making under uncertainty in high dimensional state spaces
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Hybrid control trajectory optimization under uncertainty
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Continuous State-Action-Observation POMDPs for Trajectory Planning with Bayesian Optimisation
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Contingent Contact-Based Motion Planning
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Integrating Human-Provided Information into Belief State Representation Using Dynamic Factorization
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Path Planning for Surgery Robot with Bidirectional Continuous Tree Search and Neural Network
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Driving Through Ghosts: Behavioral Cloning with False Positives
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Safe and Effective Picking Paths in Clutter given Discrete Distributions of Object Poses
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Task Planning with Belief Behavior Trees
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Homology-Class Guided Rapidly-Exploring Random Tree For Belief Space Planning
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Dynamic Replanning with Posterior Sampling
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Constrained Iterative LQG for Real-Time Chance-Constrained Gaussian Belief Space Planning
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SURESTEP: An Uncertainty-Aware Trajectory Optimization Framework to Enhance Visual Tool Tracking for Robust Surgical Automation
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From Footprints to Beliefprints: Motion Planning under Uncertainty for Maneuvering Automated Vehicles in Dense Scenarios
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Motion planning under perception and control uncertainties with Space Exploration Guided Heuristic Search
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Active Perception and Control From Temporal Logic Specifications
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A Dual-Control Effect Preserving Formulation for Nonlinear Output-Feedback Stochastic Model Predictive Control With Constraints
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Information Control Barrier Functions: Preventing Localization Failures in Mobile Systems Through Control
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Reinforcement Learning-Enhanced Belief-Space Model Predictive Control for Motion Planning Under Uncertainty
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No Correlations Involved: Decision Making Under Uncertainty in a Conservative Sparse Information Space
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C-OPT: Coverage-Aware Trajectory Optimization Under Uncertainty
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Computationally Efficient Belief Space Planning via Augmented Matrix Determinant Lemma and Reuse of Calculations
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Where to Look? Predictive Perception With Applications to Planetary Exploration
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Getting Robots Unfrozen and Unlost in Dense Pedestrian Crowds
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Information-Guided Robotic Maximum Seek-and-Sample in Partially Observable Continuous Environments
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Belief Space Planning for Mobile Robots With Range Sensors Using iLQG
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Uncertainty-Constrained Differential Dynamic Programming in Belief Space for Vision Based Robots
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FT-BSP: Focused Topological Belief Space Planning
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The Harmonic Exponential Filter for Nonparametric Estimation on Motion Groups
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A Simple Visual-Servoing Task on a Low-Accuracy, Low-Cost Arm: An Experimental Comparison Between Belief Space Planning and Proportional-Integral-Derivative Controllers
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3D-belief space planning for underwater mobile grasping
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Distributed BSP Control Methods for Underwater Collective Manipulation
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Motion planning in the belief space for compliant behaviour of a diver companion robot
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Navigation of Partially Observable Quadrotor in Smart Cities Based on UCT
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Stochastic Extended LQR for Optimization-Based Motion Planning Under Uncertainty
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Fast and Bounded Probabilistic Collision Detection for High-DOF Trajectory Planning in Dynamic Environments
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Simultaneous Control in Belief Space for Circular Insertion in Precision Assembly
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Stochastic Optimal Control for Multivariable Dynamical Systems Using Expectation Maximization
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Planning Reliable Paths With Pose SLAM
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High-Frequency Replanning Under Uncertainty Using Parallel Sampling-Based Motion Planning
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Multiobjective Path Planning: Localization Constraints and Collision Probability
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SLAP: Simultaneous Localization and Planning Under Uncertainty via Dynamic Replanning in Belief Space
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Stochastic Motion Planning Under Partial Observability for Mobile Robots With Continuous Range Measurements
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Stochastic Dynamic Games in Belief Space
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Gaussian Belief Space Path Planning for Minimum Sensing Navigation
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A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers
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Simplified Continuous High-Dimensional Belief Space Planning With Adaptive Probabilistic Belief-Dependent Constraints
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Measurement Simplification in $\rho$-POMDP with Performance Guarantees
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Multi-Agent Reinforcement Learning-Based Resource Allocation for UAV Networks
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Model Predictive Control with a Visuomotor System for Physics-based Character Animation
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LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information
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Motion planning under uncertainty using iterative local optimization in belief space
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Integrated task and motion planning in belief space
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FIRM: Sampling-based feedback motion-planning under motion uncertainty and imperfect measurements
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Integrated perception and planning in the continuous space: A POMDP approach
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Planning in the continuous domain: A generalized belief space approach for autonomous navigation in unknown environments
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Pre- and post-contact policy decomposition for planar contact manipulation under uncertainty
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Robust belief space planning under intermittent sensing via a maximum eigenvalue-based bound
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Human-robot mutual adaptation in collaborative tasks: Models and experiments
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Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions
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Funnel libraries for real-time robust feedback motion planning
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No belief propagation required: Belief space planning in high-dimensional state spaces via factor graphs, the matrix determinant lemma, and re-use of calculation
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Provably Safe Robot Navigation with Obstacle Uncertainty
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Leveraging experience for robust, adaptive nonlinear MPC on computationally constrained systems with time-varying state uncertainty
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General-purpose incremental covariance update and efficient belief space planning via a factor-graph propagation action tree
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