SOTAVerified

Motion Planning

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

Papers

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Showing 301–325 of 920 papers

TitleStatusHype
A Survey of Federated Learning for Connected and Automated Vehicles—0
Constrained Gaussian Process Motion Planning via Stein Variational Newton Inference—0
Constant-time Motion Planning with Anytime Refinement for Manipulation—0
A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles—0
A Generative System for Robot-to-Human Handovers: from Intent Inference to Spatial Configuration Imagery—0
Connected Autonomous Vehicle Motion Planning with Video Predictions from Smart, Self-Supervised Infrastructure—0
Conformal Temporal Logic Planning using Large Language Models—0
A Specification-Guided Framework for Temporal Logic Control of Nonlinear Systems—0
Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions—0
A Framework for Probabilistic Generic Traffic Scene Prediction—0
On-line Motion Planning Using Bernstein Polynomials for Enhanced Target Localization in Autonomous Vehicles—0
Confidence-rich grid mapping—0
Conditional Generative Neural System for Probabilistic Trajectory Prediction—0
A Schema-aware Logic Reformulation for Graph Reachability—0
Computational Tradeoff in Minimum Obstacle Displacement Planning for Robot Navigation—0
On trajectory design from motion primitives for near time-optimal transitions for systems with oscillating internal dynamics—0
A Framework for Learning Scoring Rules in Autonomous Driving Planning Systems—0
A Framework for Guided Motion Planning—0
Composing Task-Agnostic Policies with Deep Reinforcement Learning—0
General-Purpose Aerial Intelligent Agents Empowered by Large Language Models—0
Generalized Object Search—0
Composing Diverse Policies for Temporally Extended Tasks—0
ArticuBot: Learning Universal Articulated Object Manipulation Policy via Large Scale Simulation—0
Generalizability of Graph Neural Networks for Decentralized Unlabeled Motion Planning—0
Gaussian Process Constraint Learning for Scalable Chance-Constrained Motion Planning from Demonstrations—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified