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E-Graphs: Bootstrapping Planning with Experience Graphs
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-36460-9_27openalex-snapshot
A Single-Query Bi-Directional Probabilistic Roadmap Planner with Lazy Collision Checking
inferredcites →https://doi.org/10.1007/978-3-540-45135-8_23openalex-snapshot
Real-Time Randomized Path Planning for Robot Navigation
inferredcites →https://doi.org/10.1109/70.508439openalex-snapshot
Probabilistic roadmaps for path planning in high-dimensional configuration spaces
inferredcites →https://doi.org/10.1109/icra.2011.5980550openalex-snapshot
Planning for Manipulation with Adaptive Motion Primitives
inferredcites →https://doi.org/10.1109/irds.2002.1041624openalex-snapshot
Real-time randomized path planning for robot navigation
inferredcites →https://doi.org/10.1109/iros.2007.4399364openalex-snapshot
Transfer of policies based on trajectory libraries
inferredcites →https://doi.org/10.1109/iros.2007.4399542openalex-snapshot
Learning humanoid reaching tasks in dynamic environments
inferredcites →https://doi.org/10.1109/iros.2009.5354018openalex-snapshot
Standing balance control using a trajectory library
inferredcites →https://doi.org/10.1109/robot.2006.1642212openalex-snapshot
Policies based on trajectory libraries
inferredcites →https://doi.org/10.1109/robot.2007.363553openalex-snapshot
Multipartite RRTs for Rapid Replanning in Dynamic Environments
inferredcites →https://doi.org/10.1184/r1/6556976openalex-snapshot
Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach
inferredcites →https://doi.org/10.15607/rss.2009.v.012openalex-snapshot
Planning motion in environments with similar obstacles
inferredcites →https://doi.org/10.7551/mitpress/8727.003.0013openalex-snapshot
Planning Motion in Environments with Similar Obstacles
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Learning to Generate Cost-to-Go Functions for Efficient Motion Planning
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Effort Informed Roadmaps (EIRM*): Efficient Asymptotically Optimal Multiquery Planning by Actively Reusing Validation Effort
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Beyond Geometric Path Planning: Learning Context-Driven Trajectory Preferences via Sub-optimal Feedback
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Learning to plan for constrained manipulation from demonstrations
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Experience Learning From Basic Patterns for Efficient Robot Navigation in Indoor Environments
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Solving the motion planning problem using learning experience through case-based reasoning and machine learning algorithms
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Learning from experience for rapid generation of local car maneuvers
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Shared representations of actions for alternative suggestion with incomplete information
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Survey of optimal motion planning
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Improving Solution Quality for Experience-Based Framework Through Clustering Algorithms
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Anytime incremental planning with E-Graphs
inferred← citeshttps://doi.org/10.1109/icra.2015.7139283openalex-snapshot
Speeding up heuristic computation in planning with Experience Graphs
inferred← citeshttps://doi.org/10.1109/icra.2015.7139284openalex-snapshot
Experience-based planning with sparse roadmap spanners
inferred← citeshttps://doi.org/10.1109/icra.2015.7139695openalex-snapshot
Motion planning and irreducible trajectories
inferred← citeshttps://doi.org/10.1109/icra.2015.7139971openalex-snapshot
A web-based infrastructure for recording user demonstrations of mobile manipulation tasks
inferred← citeshttps://doi.org/10.1109/icra.2017.7989327openalex-snapshot
Learning to guide task and motion planning using score-space representation
inferred← citeshttps://doi.org/10.1109/icra.2017.7989431openalex-snapshot
Adaptive motion planning with high-dimensional mixture models
inferred← citeshttps://doi.org/10.1109/icra.2017.7989468openalex-snapshot
Parts assembly planning under uncertainty with simulation-aided physical reasoning
inferred← citeshttps://doi.org/10.1109/icra.2019.8793580openalex-snapshot
Safe and Efficient High Dimensional Motion Planning in Space-Time with Time Parameterized Prediction
inferred← citeshttps://doi.org/10.1109/icra.2019.8793942openalex-snapshot
Visual Repetition Sampling for Robot Manipulation Planning
inferred← citeshttps://doi.org/10.1109/icra.2019.8794317openalex-snapshot
Using Local Experiences for Global Motion Planning
inferred← citeshttps://doi.org/10.1109/icra40945.2020.9197015openalex-snapshot
Learning Heuristic A: Efficient Graph Search using Neural Network
inferred← citeshttps://doi.org/10.1109/icra46639.2022.9811915openalex-snapshot
Kinematic Transfer Learning of Sampling Distributions for Manipulator Motion Planning
inferred← citeshttps://doi.org/10.1109/icra48506.2021.9561104openalex-snapshot
Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions
inferred← citeshttps://doi.org/10.1109/icra48506.2021.9561563openalex-snapshot
Alternative Paths Planner (APP) for Provably Fixed-time Manipulation Planning in Semi-structured Environments
inferred← citeshttps://doi.org/10.1109/icra48506.2021.9561672openalex-snapshot
Cost-to-Go Function Generating Networks for High Dimensional Motion Planning
inferred← citeshttps://doi.org/10.1109/icra48506.2021.9561928openalex-snapshot
Fast Replanning Multi-Heuristic A
inferred← citeshttps://doi.org/10.1109/icra57147.2024.10611675openalex-snapshot
Constant-time Motion Planning with Anytime Refinement for Manipulation
inferred← citeshttps://doi.org/10.1109/ictc55196.2022.9952449openalex-snapshot
Efficient Extreme Motion Planning by Learning from Experience
inferred← citeshttps://doi.org/10.1109/iros.2016.7759197openalex-snapshot
Experience-based path planning for mobile robots exploiting user preferences
inferred← citeshttps://doi.org/10.1109/iros.2016.7759232openalex-snapshot
Motion planning with diffusion maps
inferred← citeshttps://doi.org/10.1109/iros.2017.8206116openalex-snapshot
Repetition sampling for efficiently planning similar constrained manipulation tasks
inferred← citeshttps://doi.org/10.1109/iros.2017.8206232openalex-snapshot
Science-aware exploration using entropy-based planning
inferred← citeshttps://doi.org/10.1109/iros.2018.8593977openalex-snapshot
Leveraging Precomputation with Problem Encoding for Warm-Starting Trajectory Optimization in Complex Environments
inferred← citeshttps://doi.org/10.1109/iros47612.2022.9981906openalex-snapshot
Reachability Based Trajectory Generation Combining Global Graph Search in Task Space and Local Optimization in Configuration Space
inferred← citeshttps://doi.org/10.1109/iros47612.2022.9982237openalex-snapshot
LTR*: Rapid Replanning in Executing Consecutive Tasks with Lazy Experience Graph
inferred← citeshttps://doi.org/10.1109/iros51168.2021.9636565openalex-snapshot
Online High-Level Model Estimation for Efficient Hierarchical Robot Navigation
inferred← citeshttps://doi.org/10.1109/iros55552.2023.10341264openalex-snapshot
Efficient Path Planning In Manipulation Planning Problems by Actively Reusing Validation Effort
inferred← citeshttps://doi.org/10.1109/lra.2016.2590581openalex-snapshot
Using a Compliant, Unactuated Tail to Manipulate Objects
inferred← citeshttps://doi.org/10.1109/lra.2018.2856925openalex-snapshot
The Repetition Roadmap for Repetitive Constrained Motion Planning
inferred← citeshttps://doi.org/10.1109/lra.2018.2856927openalex-snapshot
Efficient Sampling With Q-Learning to Guide Rapidly Exploring Random Trees
inferred← citeshttps://doi.org/10.1109/lra.2019.2894861openalex-snapshot
Learning Feasibility for Task and Motion Planning in Tabletop Environments
inferred← citeshttps://doi.org/10.1109/lra.2020.2972893openalex-snapshot
Memory of Motion for Warm-Starting Trajectory Optimization
inferred← citeshttps://doi.org/10.1109/lra.2021.3063063openalex-snapshot
Path Planning for Manipulation Using Experience-Driven Random Trees
inferred← citeshttps://doi.org/10.1109/lra.2021.3097061openalex-snapshot
Designing Human-Robot Coexistence Space
inferred← citeshttps://doi.org/10.1109/lra.2023.3309592openalex-snapshot
Preprocessing-Based Planning for Utilizing Contacts in Semi-Structured High-Precision Insertion Tasks
inferred← citeshttps://doi.org/10.1109/lra.2026.3656775openalex-snapshot
Situationally-Aware Path Planning Exploiting 3D Scene Graphs
inferred← citeshttps://doi.org/10.1109/robio.2017.8324822openalex-snapshot
A novel swarm robot simulation platform for warehousing logistics
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The Representation of Weighted Action-Coupled Semantic Network and Spreading Activation Model for Improvisational Action
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Learning the Problem-Optimum Map: Analysis and Application to Global Optimization in Robotics
inferred← citeshttps://doi.org/10.1155/2018/4358747openalex-snapshot
Robot Motion Planning Method Based on Incremental High‐Dimensional Mixture Probabilistic Model
inferred← citeshttps://doi.org/10.1177/0278364915581193openalex-snapshot
Learning preferences for manipulation tasks from online coactive feedback
inferred← citeshttps://doi.org/10.1177/0278364916640908openalex-snapshot
Fast probabilistic collision checking for sampling-based motion planning using locality-sensitive hashing
inferred← citeshttps://doi.org/10.1177/02783649211027194openalex-snapshot
Provably Constant-time Planning and Re-planning for Real-time Grasping Objects off a Conveyor Belt
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Learning to Plan for Constrained Manipulation from Demonstrations
inferred← citeshttps://doi.org/10.15607/rss.2020.xvi.071openalex-snapshot
Nonparametric Motion Retargeting for Humanoid Robots on Shared Latent Space
inferred← citeshttps://doi.org/10.1609/aiide.v12i1.12864openalex-snapshot
Demonstration-Based Training of Non-Player Character Tactical Behaviors
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Towards Adaptability of Demonstration-Based Training of NPC Behavior
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Learning to Avoid Local Minima in Planning for Static Environments
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Provable Indefinite-Horizon Real-Time Planning for Repetitive Tasks
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Generalized Lazy Search for Robot Motion Planning:Interleaving Search and Edge Evaluation via Event-Based Toggles
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Speeding Up Search-Based Motion Planning using Expansion Delay Heuristics
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Accelerating Search-Based Planning for Multi-Robot Manipulation by Leveraging Online-Generated Experiences
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E-Graphs: Bootstrapping Planning with Experience Graphs
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Feasibility Study: Using Highways for Bounded-Suboptimal Multi-Agent Path Finding
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Learning to Search More Efficiently from Experience: A Multi-heuristic Approach
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Abstracts of Papers Presented at SoCS 2016 in the Previously Published Paper Track
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Rapid Randomized Restarts for Multi-Agent Path Finding Solvers
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Research on the Path Planning Algorithm of a Manipulator Based on GMM/GMR-MPRM
inferred← citeshttps://doi.org/10.3390/electronics7120395openalex-snapshot
Learning the Metric of Task Constraint Manifolds for Constrained Motion Planning
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Концепт «Бог» У Тексті Нового Завіту
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Human-Scale Mobile Manipulation using RoMan
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Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment Using Fuzzy Logic and Online Learning
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