Robot Navigation

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Robot navigation combines sensing and localization with route planning and motion control, from indoor mobile robots and legged platforms to drones, vehicles, and medical devices. Common approaches include SLAM and geometric planners such as A* and model-predictive control, alongside reinforcement learning, imitation learning, and vision-language policies that use semantic maps, memory, or predicted futures. Methods are tested in simulation and on physical robots, with benchmarks such as Habitat HM3D and MP3D for object navigation and R2R-CE for language-guided routes. A central challenge is making long-horizon decisions that remain safe and efficient when perception is uncertain, environments change, and policies transfer from simulation to real robots.

Latest papers

557 papers103 papers in the last four weeks, up 29% on the four weeks before. 0.6% of all new papers.

SAFER-Nav: Enhancing Safety for Visual Robot Navigation via Segmentation-Aware Fine-Tuning
Jun 10, 2026Geonyeong Ko, Giung Lee, Changjoo NamRobot Policy Learning Trajectory Generation
Dept. of Electronic Engineering, Sogang University, Seoul, Korea · Dept. of Computer Science, Rice University, Houston, TX, USA · Vertical Labs, Co., Ltd., Seoul, Korea
Deep Learning-Based Lunar Crater Terrain Relative Navigation
Jun 10, 2026Batu Candan, Simone ServadioRemote Sensing Image Understanding Robot Navigation
Aerospace Engineering Department · Iowa State University · Ames, Iowa, USA
AllDayNav: Lifelong Navigation via Real-World Reinforcement Learning
Jun 9, 2026Hang Yin, Yinan Liang, Jiazhao Zhang +4RL for Robotics Continual Robot Learning
Tsinghua University, Beijing 100084, China · Galbot Robotics, Beijing, China · Peking University, Beijing 100871, China +1
AgniNav: Configuration-Driven Cross-Embodiment Local Planning for Robot Navigation
Jun 9, 2026Tianhao Zang, Siwei Cheng, Haidong Huang +2Robot Navigation Safe Robot Navigation
Eastern Institute of Technology, Ningbo, China · University of Nottingham, Nottingham, UK · College of Information Science and Technology, Eastern Institute of Technology, Ningbo, P. R. China. +3
GUIDE: Goal-Initialized Directional Understanding for End-to-End Legged Navigation
Jun 9, 2026Liang Wang, Jin Jin, KanZhong Yao +6Robot Navigation RL for Legged Locomotion
Institute of Cyber-Systems and Control, Zhejiang University · Institute of Artificial Intelligence (TeleAI), China Telecom · Oxford Robotics Institute, University of Oxford +2
GuideWalk: Learning Unified Autonomous Navigation and Locomotion for Humanoid Robots across Versatile Terrains
Jun 9, 2026Haoxuan Han, Chen Chen, Linao Gong +6Humanoid Robot Locomotion Robot Navigation
Harbin Institute of Technology · Leju Robotics
Bayesian Optimization for Learning Nonlinear MPC in Autonomous Agent Navigation
Jun 8, 2026Lorenzo Ortolani, Gabriel Voss, Gabriele Beltrami +2Constrained Motion Planning Nonlinear MPC
Talos Robotics AI Milan, Italy
VGP-Nav: Metric-Aware Visual Geometric Perception for Robot Navigation
Jun 8, 2026Hewei Pan, Weiye Zhu, Zekai Zhang +4Robot Navigation Robot Localization
Southern University of Science and Technology, Shenzhen, China. · MBZUAI, Abu Dhabi, UAE. · Shenzhen University, Shenzhen, China. +1
IR-SIM: A Lightweight Declarative Simulator for Navigation Learning and Benchmarking
Jun 7, 2026Ruihua Han, Shuai Wang, Chengyang Li +8Robotics Simulation Robot Navigation
The University of Hong Kong · Shenzhen Institutes of Advanced Technology · Southern University of Science and Technology +2
Beyond Waypoints: A Trajectory-Centric Waypointing Paradigm for Vision-Language Navigation
Jun 5, 2026Haoxiang Shi, Xiang Deng, Haoyu Zhang +3Trajectory Generation Diffusion-Based Planning
Harbin Institute of Technology (Shenzhen) · Pengcheng Laboratory
SCOUT: Semantic scene COverage via Uncertainty-guided Traversal
Jun 4, 2026Junyu Mao, Sara Ayoubi, Vishnu D. Sharma +2Active Perception Robot Navigation
Nokia Bell Labs, France. · Nokia Bell Labs, Murray Hill, NJ, USA.
ChronoForest: Closed-Loop Multi-Tree Diffusion Planning for Efficient Bridge Search and Route Composition
Jun 4, 2026Jungmin Seo, Jaesik ParkInference-Time Search Diffusion-Based Planning
Seoul National University Seoul, South Korea
WorldFly: A World-Model-Based Vision-Language-Action Model for UAV Navigation
Jun 4, 2026Shengtao Zheng, Kai Li, Weichen Zhang +5World Models for Robotics Robot Navigation
Tsinghua Shenzhen International Graduate School · BNRist, Tsinghua University
Robust Scene Transfer for PointGoal Navigation via Privileged Sensor Guided Contrastive Learning
Jun 3, 2026Amirhossein Zhalehmehrabi, Tiziano Tezze, Alberto Castellini +1Robot Navigation Domain Generalization
Real-World Deployment of a 5G-Connected Edge-Controlled Aerial Robot in Industrial Subterranean Mines
Jun 3, 2026Achilleas Santi Seisa, Emanuele Pagliari, Gerasimos Damigos +2Robotic Control Aerial Robotics
MineXplore: An Open-Source Reinforcement Learning Exploration Benchmark for GNSS-Denied Underground Environment
Jun 3, 2026Abhishek S, Badrikanath Praharaj, Sreeram MVRL Benchmarks Robot Navigation
BuildMachineLabs
AgenticDiffusion: Multi-View Reasoning with View-Conditioned Diffusion Planning for Vision-Based UAV Navigation
Jun 2, 2026Faryal Batool, Muhammad Ahsan Mustafa, Fawad Mehboob +2Aerial Robotics Trajectory Generation
SPADE: Sketch-guided Path Planning Augmented with Diffusion Experts
Jun 2, 2026Charbel Abi Hana, Tatiana Ghantous, Mikael Khalil +1Data Augmentation Robot Navigation
IDEALworks GmbH · IMT Atlantique · IDEALworks GmbH & Saint Joseph University of Beirut
Reliability-Guided Depth Fusion for Glare-Resilient Navigation Costmaps
Jun 2, 2026Shang-En TsaiOccupancy Grid Mapping Depth Estimation
Autonomous Navigation System for Library Service Robot Based on Unitree Go2 Edu
Jun 2, 2026Aoduo Li, Haoran Lv, Bingquan Ou +3Robot Navigation Service Robotics
Guangdong University of Technology · Shenzhen Polytechnic University
Co-training with Ego-centric Video and Demonstration for Robot Navigation Task
Jun 1, 2026Shoya Kuno, Yumo Ouchi, Kanata SuzukiMobile Robotics Robot Navigation
Spatial Robotics Research Center, Fujitsu Limited., Kanagawa 211-8588, Japan.
Closed-Form Pose Estimation of Endoluminal Medical Devices via Gradiometer-Based Electromagnetic Localization System
Jun 1, 2026Zhiwei Wu, Jiahao Luo, Yubo Pu +3Robot Navigation Object Pose Estimation
School of Automation, Beijing Institute of Technology, Beijing, 100081, China
Hierarchical Semantic-Augmented Navigation: Optimal Transport and Graph-Driven Reasoning for Vision-Language Navigation
Jun 1, 2026Xiang Fang, Wanlong Fang, Changshuo WangRobot Navigation Robotic RL
School of Software Engineering, Huazhong University of Science and Technology · Nanyang Technological University, Singapore · Interdisciplinary Graduate Programme University College London
PSG-Nav: Probabilistic Scene Graph Navigation via Multiverse Decision Making
May 31, 2026Rufeng Chen, Yue Chang, Xiaqiang Tang +2Continual Robot Learning Embodied Navigation
The Hong Kong University of Science and Technology (Guangzhou), Guangdong, China · Jilin University, Jilin, China
OSCAR: Obstacle Survival Curves for Adaptive Robot Navigation
May 31, 2026Hshmat Sahak, Aoran Jiao, Nicholas Rhinehart +1Robot Navigation Graph-Based Planning
University of Toronto, Canada
BEVIO: Efficient Bird's-Eye-View based Sparse-Update Visual-Inertial Odometry for Lunar Day-Night Navigation
May 30, 2026Mohit Singh, Shehryar Khattak, Ashish Goel +3Robot Navigation Visual Odometry
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA. · Autonomous Robots Lab at the Norwegian University of Science and Technology, Trondheim, Norway
LiftNav: Path Planning via Semantic Lifting in TSDF-Guided Gaussian Splatting
May 29, 2026Hannah Schieber, Dominik Frischmann, Victor Schaack +2Trajectory Optimization Robot Navigation
Technical University of Munich, Human-Centered Computing and Extended Reality Lab, TUM University Hospital, Clinic for Orthopedics and Sports Orthopedics, Munich Institute of Robotics and Machine Intelligence (MIRMI) · Technical University of Munich, Learning Systems and Robotics Lab, Munich Institute of Robotics and Machine Intelligence (MIRMI)
TARIC: Memory-Augmented Traversability-Aware Outdoor VLN under Interrupted Semantic Cues
May 29, 2026Tianle Zeng, Hanjing Ye, Jianwei Peng +3Robot Navigation Vision-Language Navigation
Shenzhen Key Laboratory of Robotics and Computer Vision, Southern University of Science and Technology, Shenzhen, China. · CKS Robotics Institute, Hong Kong University of Science and Technology, Hong Kong SAR, China. · College of Electrical and Information Engineering, Hunan University, Hunan, China.
Learning-Based Navigation for Indoor Mobile Robots
May 28, 2026Tri-Tin Nguyen, Tien-Dat Nguyen, Gia-Uy Le +2Robot Navigation Motion Planning
Faculty of Electrical and Electronic Engineering, Ho Chi Minh City University of Technology, VNU-HCM Ho Chi Minh City, Vietnam
Fisher-Preserving Guidance: Training-Free Manifold Constraints for Safe Diffusion Control
May 28, 2026Hao Ren, Zetong Bi, Yiming Zeng +5Diffusion Model Guidance Diffusion-Based Planning
Sun Yat-sen University, Guangzhou, China · Insta360 Research, Shenzhen, China

Jun 10, 2026J/K move · Enter open · S save

SAFER-Nav: Enhancing Safety for Visual Robot Navigation via Segmentation-Aware Fine-Tuning

Geonyeong Ko, Giung Lee, Changjoo Nam

Dept. of Electronic Engineering, Sogang University, Seoul, Korea · Dept. of Computer Science, Rice University, Houston, TX, USA · Vertical Labs, Co., Ltd., Seoul, Korea

Robot Policy Learning Trajectory Generation Robot Navigation Safe Robot Navigation Robot Safety Visual Robot Navigation

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Vision-based navigation models, particularly foundation models, generate viable trajectories from RGB observations alone. However, even state-of-the-art transformer- and diffusion-based policies struggle to generalize in unfamiliar deployment environments containing unseen obstacles or shifted conditions. The resulting trajectories often remain goal-directed but unsafe. Existing efforts improve safety through external trajectory correction or internal geometric priors, yet the resulting policies are not trained to explicitly represent obstacle boundaries or traversable free-space structure. To address this, we propose a navigation model that incorporates these structures directly into the policy via fine-tuning and is designed to be compatible with diverse RGB-based backbones. Across multiple robot platforms, indoor environments, and static and dynamic obstacle scenarios, our method reduces collision frequency relative to ViNT, NoMaD, and their CARE-augmented variants while maintaining goal-reaching performance.