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Planning motion in environments with similar obstacles

https://doi.org/10.15607/rss.2009.v.012

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/10991541_25openalex-snapshot

A Machine Learning Approach for Feature-Sensitive Motion Planning

inferredcites →https://doi.org/10.1007/978-1-4471-3702-3_4openalex-snapshot

State of the Art in Shape Matching

inferredcites →https://doi.org/10.1007/978-1-4613-8997-2_20openalex-snapshot

Spatial Planning: A Configuration Space Approach

inferredcites →https://doi.org/10.1007/978-3-540-68405-3_18openalex-snapshot

RESAMPL: A Region-Sensitive Adaptive Motion Planner

inferredcites →https://doi.org/10.1007/978-3-540-68405-3_4openalex-snapshot

Incremental Map Generation (IMG)

inferredcites →https://doi.org/10.1016/j.gmod.2005.11.003openalex-snapshot

Accurate Minkowski sum approximation of polyhedral models

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/iros.1999.811662openalex-snapshot

Visibility based probabilistic roadmaps

inferredcites →https://doi.org/10.1109/iros.2004.1389624openalex-snapshot

Roadmap-based motion planning in dynamic environments

inferredcites →https://doi.org/10.1109/iros.2004.1389625openalex-snapshot

A PRM-based motion planner for dynamically changing environments

inferredcites →https://doi.org/10.1109/iros.2005.1545549openalex-snapshot

Safe motion planning in dynamic environments

inferredcites →https://doi.org/10.1109/pg.2007.47openalex-snapshot

Radiometric Compensation through Inverse Light Transport

inferredcites →https://doi.org/10.1109/pg.2007.49openalex-snapshot

Point-Based Minkowski Sum Boundary

inferredcites →https://doi.org/10.1109/robot.1996.503582openalex-snapshot

A randomized roadmap method for path and manipulation planning

inferredcites →https://doi.org/10.1109/robot.1997.619371openalex-snapshot

Path planning in expansive configuration spaces

inferredcites →https://doi.org/10.1109/robot.1999.772447openalex-snapshot

The Gaussian sampling strategy for probabilistic roadmap planners

inferredcites →https://doi.org/10.1109/robot.1999.772448openalex-snapshot

MAPRM: a probabilistic roadmap planner with sampling on the medial axis of the free space

inferredcites →https://doi.org/10.1109/robot.2002.1014238openalex-snapshot

An incremental learning approach to motion planning with roadmap management

inferredcites →https://doi.org/10.1109/robot.2003.1242285openalex-snapshot

The bridge test for sampling narrow passages with probabilistic roadmap planners

inferredcites →https://doi.org/10.1109/robot.2005.1570589openalex-snapshot

C-space Subdivision and Integration in Feature-Sensitive Motion Planning

inferredcites →https://doi.org/10.1109/robot.2006.1642056openalex-snapshot

Anytime path planning and replanning in dynamic environments

inferredcites →https://doi.org/10.1109/robot.2006.1642072openalex-snapshot

Planning motion in completely deformable environments

inferredcites →https://doi.org/10.1109/smi.2004.1314504openalex-snapshot

The princeton shape benchmark

inferredcites →https://doi.org/10.1109/tc.1983.1676196openalex-snapshot

Spatial Planning: A Configuration Space Approach

inferredcites →https://doi.org/10.1109/tro.2005.851378openalex-snapshot

Roadmap-based motion planning in dynamic environments

inferredcites →https://doi.org/10.1145/1109557.1109587openalex-snapshot

Self-improving algorithms

inferredcites →https://doi.org/10.1145/1377676.1377700openalex-snapshot

Self-improving algorithms for delaunay triangulations

inferredcites →https://doi.org/10.1145/997817.997889openalex-snapshot

Approximate convex decomposition

inferredcites →https://doi.org/10.1177/027836402128964170openalex-snapshot

A Framework for Real-time Path Planning in Changing Environments

inferredcites →https://doi.org/10.1177/027836499801700706openalex-snapshot

Motion Planning in Dynamic Environments Using Velocity Obstacles

inferredcites →https://doi.org/10.1201/9781439863886-19openalex-snapshot

OBPRM: An Obstacle-Based PRM for 3D Workspaces

inferredcites →https://doi.org/10.1201/9781439864135-33openalex-snapshot

A Kinematics-Based Probabilistic Roadmap Method for Closed Chain Systems

inferredcites →https://doi.org/10.1201/9781439864135-43openalex-snapshot

Rapidly-Exploring Random Trees: Progress and Prospects

inferredcites →https://doi.org/10.15607/rss.2005.i.015openalex-snapshot

Toward Optimal Configuration Space Sampling

inferredcites →https://doi.org/10.15607/rss.2006.ii.036openalex-snapshot

Elastic Roadmaps: Globally Task-Consistent Motion for Autonomous Mobile Manipulation in Dynamic Environments

inferredcites →https://doi.org/10.15607/rss.2007.iii.006openalex-snapshot

Predicting Partial Paths from Planning Problem Parameters

inferredcites →https://doi.org/10.15607/rss.2008.iv.013openalex-snapshot

Hybrid Motion Planning Using Minkowski Sums

inferredcites →https://doi.org/10.5555/1109557.1109587openalex-snapshot

Self-improving algorithms

inferredcites →https://doi.org/10.7551/mitpress/8344.003.0017openalex-snapshot

Hybrid Motion Planning Using Minkowski Sums

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s10514-019-09852-5openalex-snapshot

Real-time robot path planning from simple to complex obstacle patterns via transfer learning of options

inferred← citeshttps://doi.org/10.1007/s10846-017-0739-7openalex-snapshot

Experience Learning From Basic Patterns for Efficient Robot Navigation in Indoor Environments

inferred← citeshttps://doi.org/10.1016/j.robot.2017.08.014openalex-snapshot

User preferred behaviors for robot navigation exploiting previous experiences

inferred← citeshttps://doi.org/10.1080/01691864.2018.1465849openalex-snapshot

Gaussian mixture spline trajectory: learning from a dataset, generating trajectories without one

inferred← citeshttps://doi.org/10.1109/case56687.2023.10260337openalex-snapshot

Motion Planning to Cartesian Targets Leveraging Large-Scale Dynamic Roadmaps

inferred← citeshttps://doi.org/10.1109/etfa.2013.6648033openalex-snapshot

Manipulation tasks with a dual arm system including obstacles removing

inferred← citeshttps://doi.org/10.1109/etfa.2015.7301516openalex-snapshot

Comparison of motion planners in an environment with removable obstacles

inferred← citeshttps://doi.org/10.1109/icarsc.2017.7964088openalex-snapshot

Real-time robot path planning around complex obstacle patterns through learning and transferring options

inferred← citeshttps://doi.org/10.1109/icra.2012.6224742openalex-snapshot

A robot path planning framework that learns from experience

inferred← citeshttps://doi.org/10.1109/icra.2013.6630909openalex-snapshot

Anytime incremental planning with E-Graphs

inferred← citeshttps://doi.org/10.1109/icra.2015.7139286openalex-snapshot

Lazy validation of Experience Graphs

inferred← citeshttps://doi.org/10.1109/icra.2015.7139771openalex-snapshot

Folding and unfolding origami tessellation by reusing folding path

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.2019.8794317openalex-snapshot

Using Local Experiences for Global Motion Planning

inferred← citeshttps://doi.org/10.1109/icra46639.2022.9812076openalex-snapshot

Learning to Retrieve Relevant Experiences for 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/icra57147.2024.10610790openalex-snapshot

Motion Memory: Leveraging Past Experiences to Accelerate Future Motion Planning

inferred← citeshttps://doi.org/10.1109/iros.2011.6094436openalex-snapshot

Finding critical changes in dynamic configuration spaces

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/lra.2021.3097061openalex-snapshot

Designing Human-Robot Coexistence Space

inferred← citeshttps://doi.org/10.1109/robot.2010.5509825openalex-snapshot

Trajectory prediction in cluttered voxel environments

inferred← citeshttps://doi.org/10.1109/tpami.2013.67openalex-snapshot

Minimum Near-Convex Shape Decomposition

inferred← citeshttps://doi.org/10.1109/tro.2016.2623345openalex-snapshot

Learning the Problem-Optimum Map: Analysis and Application to Global Optimization in Robotics

inferred← citeshttps://doi.org/10.1115/detc2014-35561openalex-snapshot

Collision Prediction: Conservative Advancement Among Obstacles With Unknown Motion

inferred← citeshttps://doi.org/10.1177/0278364919848837openalex-snapshot

Learning to guide task and motion planning using score-space representation

inferred← citeshttps://doi.org/10.15607/rss.2012.viii.043openalex-snapshot

E-Graphs: Bootstrapping Planning with Experience Graphs

inferred← citeshttps://doi.org/10.48550/arxiv.1610.02573openalex-snapshot

Proceedings of the 1st International Workshop on Robot Learning and Planning (RLP 2016)

inferred← citeshttps://doi.org/10.48550/arxiv.2008.11174openalex-snapshot

Learning Obstacle Representations for Neural Motion Planning

inferred← citeshttps://doi.org/10.5755/j01.itc.50.2.28234openalex-snapshot

Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment Using Fuzzy Logic and Online Learning

inferred← citeshttps://doi.org/10.6109/jicce.2014.12.2.116openalex-snapshot

Heuristics for Motion Planning Based on Learning in Similar Environments

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