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Robot Navigation
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The fundamental objective of mobile Robot Navigation is to arrive at a goal position without collision. The mobile robot is supposed to be aware of obstacles and move freely in different working scenarios.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Optimising 4th-Order Runge-Kutta Methods: A Dynamic Heuristic Approach for Efficiency and Low Storage
HRIBench: Benchmarking Vision-Language Models for Real-Time Human Perception in Human-Robot Interaction
NaviAgent: Bilevel Planning on Tool Dependency Graphs for Function Calling
GeNIE: A Generalizable Navigation System for In-the-Wild Environments
ADA-DPM: A Neural Descriptors-based Adaptive Noise Point Filtering Strategy for SLAM
Adversarial Attacks and Detection in Visual Place Recognition for Safer Robot Navigation
Human-Robot Navigation using Event-based Cameras and Reinforcement Learning
Data-Driven Prediction of Dynamic Interactions Between Robot Appendage and Granular Material
LLM-driven Indoor Scene Layout Generation via Scaled Human-aligned Data Synthesis and Multi-Stage Preference Optimization
Deep Equivariant Multi-Agent Control Barrier Functions
Multimodal Spatial Language Maps for Robot Navigation and Manipulation
Astra: Toward General-Purpose Mobile Robots via Hierarchical Multimodal Learning
SGN-CIRL: Scene Graph-based Navigation with Curriculum, Imitation, and Reinforcement Learning
Olfactory Inertial Odometry: Methodology for Effective Robot Navigation by Scent
DualMap: Online Open-Vocabulary Semantic Mapping for Natural Language Navigation in Dynamic Changing Scenes
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration
Reducing Latency in LLM-Based Natural Language Commands Processing for Robot Navigation
Efficient Dynamic Shielding for Parametric Safety Specifications
Movable-Element STARS-Assisted Near-Field Wideband Communications
Consistency-based Abductive Reasoning over Perceptual Errors of Multiple Pre-trained Models in Novel Environments
Skip-Thinking: Chunk-wise Chain-of-Thought Distillation Enable Smaller Language Models to Reason Better and Faster
Reinforcement Learning for Ballbot Navigation in Uneven Terrain
Enhancing Robot Navigation Policies with Task-Specific Uncertainty Managements
UPTor: Unified 3D Human Pose Dynamics and Trajectory Prediction for Human-Robot Interaction
SayCoNav: Utilizing Large Language Models for Adaptive Collaboration in Decentralized Multi-Robot Navigation
Ranking-aware Continual Learning for LiDAR Place Recognition
PhysNav-DG: A Novel Adaptive Framework for Robust VLM-Sensor Fusion in Navigation Applications
Semantic Intelligence: Integrating GPT-4 with A Planning in Low-Cost Robotics
Deep Learning-Based Multi-Modal Fusion for Robust Robot Perception and Navigation
Integration of a Graph-Based Path Planner and Mixed-Integer MPC for Robot Navigation in Cluttered Environments
Robust Output-Feedback MPC for Nonlinear Systems with Applications to Robotic Exploration
Development of a PPO-Reinforcement Learned Walking Tripedal Soft-Legged Robot using SOFA
FindAnything: Open-Vocabulary and Object-Centric Mapping for Robot Exploration in Any Environment
Neural Fidelity Calibration for Informative Sim-to-Real Adaptation
Localization Meets Uncertainty: Uncertainty-Aware Multi-Modal Localization
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