SOTAVerified

Motion Planning

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–175 of 920 papers

TitleStatusHype
Multi-Robot Motion Planning with Diffusion ModelsCode2
A Schema-aware Logic Reformulation for Graph Reachability—0
Stochasticity in Motion: An Information-Theoretic Approach to Trajectory Prediction—0
Towards Generalizable Vision-Language Robotic Manipulation: A Benchmark and LLM-guided 3D PolicyCode2
LASMP: Language Aided Subset Sampling Based Motion PlannerCode0
ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AICode7
COLLAGE: Collaborative Human-Agent Interaction Generation using Hierarchical Latent Diffusion and Language Models—0
Generalizability of Graph Neural Networks for Decentralized Unlabeled Motion Planning—0
GSON: A Group-based Social Navigation Framework with Large Multimodal Model—0
Dashing for the Golden Snitch: Multi-Drone Time-Optimal Motion Planning with Multi-Agent Reinforcement LearningCode1
Blox-Net: Generative Design-for-Robot-Assembly Using VLM Supervision, Physics Simulation, and a Robot with Reset—0
Fast End-to-End Generation of Belief Space Paths for Minimum Sensing Navigation—0
RenderWorld: World Model with Self-Supervised 3D Label—0
Interpretable Responsibility Sharing as a Heuristic for Task and Motion PlanningCode0
Neural MP: A Generalist Neural Motion Planner—0
OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving—0
KiloBot: A Programming Language for Deploying Perception-Guided Industrial Manipulators at Scale—0
Fast and Modular Autonomy Software for Autonomous Racing Vehicles—0
ViIK: Flow-based Vision Inverse Kinematics Solver with Fusing Collision CheckingCode0
Target-Oriented Object Grasping via Multimodal Human Guidance—0
Edge-Cloud Collaborative Motion Planning for Autonomous Driving with Large Language Models—0
SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion PlanningCode4
A Meta-Engine Framework for Interleaved Task and Motion Planning using Topological Refinements—0
PLANRL: A Motion Planning and Imitation Learning Framework to Bootstrap Reinforcement Learning—0
Analysis of Functional Insufficiencies and Triggering Conditions to Improve the SOTIF of an MPC-based Trajectory Planner—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified