SOTAVerified

Motion Planning

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

Papers

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Showing 626–650 of 920 papers

TitleStatusHype
Designing Human-Robot Coexistence Space—0
Designing inverse dynamic controller with integral action for motion planning of surgical robot in the presence of bounded disturbances—0
DEUX: Active Exploration for Learning Unsupervised Depth Perception—0
Differentiable Constrained Imitation Learning for Robot Motion Planning and Control—0
DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability—0
Discovering Multiple Algorithm Configurations—0
Disentangled Neural Relational Inference for Interpretable Motion Prediction—0
Distance and Collision Probability Estimation from Gaussian Surface Models—0
Distilling Multi-modal Large Language Models for Autonomous Driving—0
Distributed Attack-Robust Submodular Maximization for Multi-Robot Planning—0
Distributed Safe Learning and Planning for Multi-robot Systems—0
DreamRunner: Fine-Grained Storytelling Video Generation with Retrieval-Augmented Motion Adaptation—0
Drive-R1: Bridging Reasoning and Planning in VLMs for Autonomous Driving with Reinforcement Learning—0
Driving Everywhere with Large Language Model Policy Adaptation—0
Driving Style Encoder: Situational Reward Adaptation for General-Purpose Planning in Automated Driving—0
Synthesis of Discounted-Reward Optimal Policies for Markov Decision Processes Under Linear Temporal Logic Specifications—0
Synthesis of Opacity-Enforcing Winning Strategies Against Colluded Opponent—0
Target-Oriented Object Grasping via Multimodal Human Guidance—0
Task Allocation for Multi-Robot Task and Motion Planning: a case for Object Picking in Cluttered Workspaces—0
Task and Motion Planning for Execution in the Real—0
Task-assisted Motion Planning in Partially Observable Domains—0
Task-Motion Planning for Navigation in Belief Space—0
Task-relevant Representation Learning for Networked Robotic Perception—0
T-CBF: Traversability-based Control Barrier Function to Navigate Vertically Challenging Terrain—0
Teaching Robots to Build Simulations of Themselves—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GPT-DriverCollision0.35—Unverified