SOTAVerified

Motion Planning

( Image credit: Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 651–700 of 920 papers

TitleStatusHype
Inverse reinforcement learning for autonomous navigation via differentiable semantic mapping and planning—0
Universal Adaptive Control of Nonlinear Systems—0
Forming Real-World Human-Robot Cooperation for Tasks With General Goal—0
GEM: Online Globally consistent dense elevation mapping for unstructured terrainCode1
PePScenes: A Novel Dataset and Baseline for Pedestrian Action Prediction in 3DCode0
Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions—0
Cost-to-Go Function Generating Networks for High Dimensional Motion Planning—0
Fast-reactive probabilistic motion planning for high-dimensional robots—0
Coinbot: Intelligent Robotic Coin Bag Manipulation Using Deep Reinforcement Learning And Machine Teaching—0
Leveraging Neural Network Gradients within Trajectory Optimization for Proactive Human-Robot InteractionsCode0
Unsupervised Path Regression Networks—0
Learning from Human Directional CorrectionsCode1
An End-to-end Deep Reinforcement Learning Approach for the Long-term Short-term Planning on the Frenet SpaceCode1
Relation3DMOT: Exploiting Deep Affinity for 3D Multi-Object Tracking from View Aggregation—0
C-Learning: Horizon-Aware Cumulative Accessibility EstimationCode0
Risk-Sensitive Motion Planning using Entropic Value-at-Risk—0
Reactive Human-to-Robot Handovers of Arbitrary Objects—0
Combining Reinforcement Learning with Model Predictive Control for On-Ramp MergingCode1
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects—0
Designing Human-Robot Coexistence Space—0
Decentralized Motion Planning for Multi-Robot Navigation using Deep Reinforcement LearningCode1
Learning Constrained Distributions of Robot Configurations with Generative Adversarial NetworkCode1
Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement LearningCode1
Uncertainty-Aware Constraint Learning for Adaptive Safe Motion Planning from Demonstrations—0
Task-relevant Representation Learning for Networked Robotic Perception—0
Reactive motion planning with probabilistic safety guarantees—0
Learning a Decentralized Multi-arm Motion PlannerCode1
Deep-Learning-Aided Path Planning and Map Construction for Expediting Indoor Mapping—0
Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving—0
Synthesis of Discounted-Reward Optimal Policies for Markov Decision Processes Under Linear Temporal Logic Specifications—0
Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High DimensionsCode1
Learning to Plan Optimally with Flow-based Motion Planner—0
Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational AutoencodersCode0
Planning with Learned Dynamics: Probabilistic Guarantees on Safety and Reachability via Lipschitz Constants—0
Constrained Motion Planning Networks X—0
Multi-Agent Motion Planning using Deep Learning for Space Applications—0
Reinforcement Learning Based Temporal Logic Control with Maximum Probabilistic SatisfactionCode0
Broadly-Exploring, Local-Policy Trees for Long-Horizon Task Planning—0
Projection Mapping Implementation: Enabling Direct Externalization of Perception Results and Action Intent to Improve Robot ExplainabilityCode0
Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point CloudsCode1
MADRaS : Multi Agent Driving Simulator—0
Integrated Task and Motion Planning—0
Towards Multi-Robot Task-Motion Planning for Navigation in Belief Space—0
Learning to swim in potential flowCode1
Motion Planning Combines Psychological Safety and Motion Prediction for a Sense Motive Robot—0
With Whom to Communicate: Learning Efficient Communication for Multi-Robot Collision Avoidance—0
Robust Finite-State Controllers for Uncertain POMDPs—0
Learning Equality Constraints for Motion Planning on ManifoldsCode1
Motion Planning by Reinforcement Learning for an Unmanned Aerial Vehicle in Virtual Open Space with Static Obstacles—0
Artificial Intelligence Control in 4D Cylindrical Space for Industrial Robotic ApplicationsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified