SOTAVerified

Motion Planning

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

Papers

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Showing 701–750 of 920 papers

TitleStatusHype
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
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects—0
Designing Human-Robot Coexistence Space—0
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
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 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
MADRaS : Multi Agent Driving Simulator—0
Integrated Task and Motion Planning—0
Towards Multi-Robot Task-Motion Planning for Navigation in Belief Space—0
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
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
Solution Concepts in Hierarchical Games under Bounded Rationality with Applications to Autonomous DrivingCode0
Real-time Lane detection and Motion Planning in Raspberry Pi and Arduino for an Autonomous Vehicle Prototype—0
Stochastic Model Predictive Control with a Safety Guarantee for Automated Driving: Extended Version—0
POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments—0
Path Planning Followed by Kinodynamic Smoothing for Multirotor Aerial Vehicles (MAVs)—0
T^-Lite: A Fast Time-Risk Optimal Motion Planning Algorithm for Multi-Speed Autonomous Vehicles—0
Designing inverse dynamic controller with integral action for motion planning of surgical robot in the presence of bounded disturbances—0
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations—0
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction—0
DSDNet: Deep Structured self-Driving Network—0
Neural Manipulation Planning on Constraint Manifolds—0
Near-Optimal Reactive Synthesis Incorporating Runtime Information—0
Learning the Solution Manifold in Optimization and Its Application in Motion Planning—0
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting—0
Autonomy and Unmanned Vehicles Augmented Reactive Mission-Motion Planning Architecture for Autonomous Vehicles—0
VRUNet: Multi-Task Learning Model for Intent Prediction of Vulnerable Road Users—0
Predicting Sample Collision with Neural Networks—0
Confidence-rich grid mapping—0
One Thousand and One Hours: Self-driving Motion Prediction DatasetCode0
Graph Neural Networks for Motion Planning—0
Learning Navigation Costs from Demonstration with Semantic Observations—0
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image—0
Learning Navigation Costs from Demonstrations with Semantic Observations—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified