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Motion Planning
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<span style="color:grey; opacity: 0.6">( Image credit: Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Leveraging Pre-trained Large Language Models with Refined Prompting for Online Task and Motion Planning
Learning Isometric Embeddings of Road Networks using Multidimensional Scaling
Mixed Bernstein-Fourier Approximants for Optimal Trajectory Generation with Periodic Behavior
Monocular inspection of spacecraft under illumination constraints and avoidance regions
UniPhys: Unified Planner and Controller with Diffusion for Flexible Physics-Based Character Control
Layered Multirate Control of Constrained Linear Systems
HyRRT-Connect: Bidirectional Motion Planning for Hybrid Dynamical Systems
Constrained Gaussian Process Motion Planning via Stein Variational Newton Inference
Path Database Guidance for Motion Planning
From Shadows to Safety: Occlusion Tracking and Risk Mitigation for Urban Autonomous Driving
A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspective
OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model
Predictive Traffic Rule Compliance using Reinforcement Learning
Adaptive Interactive Navigation of Quadruped Robots using Large Language Models
Energy-Aware Lane Planning for Connected Electric Vehicles in Urban Traffic: Design and Vehicle-in-the-Loop Validation
Combining Graph Attention Networks and Distributed Optimization for Multi-Robot Mixed-Integer Convex Programming
Curvature-Constrained Vector Field for Motion Planning of Nonholonomic Robots
Predicting the Road Ahead: A Knowledge Graph based Foundation Model for Scene Understanding in Autonomous Driving
PhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videos
Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning
MoManipVLA: Transferring Vision-language-action Models for General Mobile Manipulation
Iterative Motion Planning in Multi-agent Systems with Opportunistic Communication under Disturbance
Hierarchical Reinforcement Learning for Safe Mapless Navigation with Congestion Estimation
IMPACT: Intelligent Motion Planning with Acceptable Contact Trajectories via Vision-Language Models
CODEI: Resource-Efficient Task-Driven Co-Design of Perception and Decision Making for Mobile Robots Applied to Autonomous Vehicles
Finetuning Generative Trajectory Model with Reinforcement Learning from Human Feedback
Graph-Grounded LLMs: Leveraging Graphical Function Calling to Minimize LLM Hallucinations
Vi-LAD: Vision-Language Attention Distillation for Socially-Aware Robot Navigation in Dynamic Environments
Control Barrier Functions for Prescribed-time Reach-Avoid-Stay Tasks using Spatiotemporal Tubes
General-Purpose Aerial Intelligent Agents Empowered by Large Language Models
Soft Actor-Critic-based Control Barrier Adaptation for Robust Autonomous Navigation in Unknown Environments
Combating Partial Perception Deficit in Autonomous Driving with Multimodal LLM Commonsense
A Task and Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networks
T-CBF: Traversability-based Control Barrier Function to Navigate Vertically Challenging Terrain
Safety-Critical Traffic Simulation with Adversarial Transfer of Driving Intentions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.