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62 papers in the last four weeks, up 520% on the four weeks before. 0.6% of all new papers.

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LEAP: Learning Emergent Active Perception for Quadruped Navigation
Sep 15, 2026Ü. Bora Gökbakan, Stéphane Caron, Philippe SouèresRobot Navigation Active View Selection
WILLOW · Inria and DI ENS, PSL, Paris, France · ISIR +3
Visual Cue Guided Video Planning for Generalizable Robot Navigation
Sep 15, 2026Hojin Lee, Sizhe Lester Li, Maximilian Hilger +4Embodied Navigation Robot Navigation
Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich, 80797 Munich, Germany. · Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA 02139, USA. · Centre for Applied Autonomous Sensor Systems (AASS), Örebro University, 72081 Örebro, Sweden.
EgoPathBench: Evaluating Zero-Shot Egocentric Waypoint Decision-Making in Vision-Language Models
Sep 15, 2026Yang Zhao, Zhuo Chen, Xubo YangVLM Evaluation Spatial Reasoning Benchmarks
Shanghai Jiao Tong University
UDAV: Uncertainty-Driven Adaptive VLM Waypoint Planner
Sep 14, 2026Ghazal Farhani, Shabnam ShabaniUncertainty Estimation for VLA Models Trajectory Generation
The authors are with the Automotive and Surface Transportation Research Centre, National Research Council Canada, London, Ontario, Canada.
Distributed Safe Cooperative Vector Field for Trajectory Curvature Constrained Multi-Robot Systems
Sep 14, 2026Zhouru Xiao, Tao Teng, Weijia Yao +3Robot Trajectory Tracking Robot Navigation
School of Artificial Intelligence and Robotics, Hunan University, Changsha 410082, China · College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410082, China
A Hierarchical Coverage Path Planning Algorithm for Unknown Environments
Sep 14, 2026Zongyuan Shen, Haodong Liu, Gao Wang +4Robot Navigation Coverage Path Planning
College of Information Science and Technology, Jinan University, Guangzhou 510632, China. · School of Automation, Beijing Institute of Technology, Beijing 100081, China. · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.
Tuning ROS 2 for Energy-Efficient Navigation: Empirical Insights from Costmap 2D Configurations
Sep 14, 2026Michel Albonico, Andreas Wortmann, Ivano MalavoltaEnergy-Efficient Robot Locomotion Robot Navigation
Federal University of Technology - Paran´a (UTFPR), DAINF-FB, Francisco Beltr˜ao, Brazil · University of Southern Denmark (SDU), MMMI, Centre for Software Technology (CST), Vejle, Denmark · Institute for Control Eng. of Machine Tools and Manufacturing Units (ISW), University of Stuttgart, Stuttgart, Germany +1
A traffic management system for large and heterogeneous vehicles in narrow industrial environments
Sep 9, 2026Alessandro Bonetti, Silvia Proia, Simone Guidetti +1Robot Navigation Robust MAPF
Department of Sciences and Methods for Engineering (DISMI), University of Modena and Reggio Emilia, Italy · Gruppo TecnoFerrari S.p.a. con socio unico, Italy
TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model
Sep 8, 2026Anqi Li, Yuxin Chen, Zhaobo Li +4Robot Navigation Humanoid Robot Control
University of California, Berkeley · Peking University · Tsinghua University +2
DCLP++: Learning to Navigate with Footprint Clearance and Relative Motion
Sep 8, 2026Shanze Wang, Wei ZhangRobot Navigation Dynamic Obstacle Avoidance
College of Information Science and Technology, Eastern Institute of Technology, Ningbo, China · Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
EvoNav-Bench: Benchmarking Lifelong Navigation in Evolving Environments
Sep 8, 2026Xilin Wang, Guoxi Zhang, Hongming Xu +3Embodied Navigation Robot Navigation
State Key Laboratory of General Artificial Intelligence, BIGAI · 2Tsinghua University
OmniNav: Robust Long-Horizon Target Navigation in Dynamic Environments
Sep 8, 2026Yujie Tang, Meiling Wang, Jinhao Jiang +4Robot Navigation Object-Goal Navigation
School of Automation, Beijing Institute of Technology, Beijing, China.
Mini-Batch Risk-Averse Deep Q-Learning: A Robot Navigation Case Study
Sep 7, 2026Aayush Patel, Andrzej RuszczyńskiDeep Q-Learning Robot Navigation
Department of Management Science and Information Systems, Rutgers University
Singularity-Free Guiding Vector Fields on SO(3) with Designer-Specified Progression Behavior
Sep 7, 2026Jesus Bautista, Hector Garcia de MarinaRobot Navigation Feedback Control
Department of Computer Engineering, Automation and Robotics, and Institute of Mathematics (IMAG), University of Granada, Granada, Spain
MulDP: Multimodal Diffusion Policy for Autonomous Quadruped Parkour Navigation across Complex Terrains
Sep 3, 2026Kangmai Hu, Yueqi Zhang, Peng Zhai +5Robot Policy Learning Robot Navigation
College of Intelligent Robotics and Advanced Manufacturing, Fudan University, Shanghai 200433, China
Revisiting Topological Graphs for Macro Action based Closed-loop Reinforcement Learning of Vision Language Navigation in Continuous Environment
Sep 3, 2026Shuhao Ye, Sitong Mao, Yuxiang Cui +7Robot Navigation Hierarchical RL
Zhejiang University, Hangzhou, China · Huawei Technologies Co., Ltd · Zhejiang Humanoid Robot Innovation Center, Ningbo, China
Air-Ground Collaborative Vision-and-Language Navigation via Shared Bird's-Eye Maps
Sep 3, 2026Shuning Zhang, Liang Li, Yunheng Wang +3Robot Navigation UAV Navigation
Robotics and Autonomous Systems Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), China · School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, China
GAFT: Geo-Anchored Fine-Tuning for Hazard Identification from Rare Failures
Aug 31, 2026Yanran Xu, Chuanhang Qiu, Yue Wang +2Robot Navigation Vision Foundation Model Adaptation
University of Southampton, Southampton, United Kingdom
HorizonNet for visual terrain navigation
Aug 31, 2026Bertil Grelsson, Andreas Robinson, Michael Felsberg +1Robot Navigation Map-Based Localization
Computer Vision Laboratory, Department of Electrical Engineering, Linköping University, Sweden · Inception Institute of Artificial Intelligence, Abu Dhabi, UAE
Hydra: A Navigation World Action Model with Discrete Latent Planning and Continuous Flow-Matching Execution
Aug 29, 2026Mohammad Nazeri, Alexandyr Card, Samira Huber +6Kinodynamic Motion Planning World Models for Robotics
George Mason University · Kiel University · Ludwig Maximilian University Munich +1
UrbanGround: From Local Perception to Spatial Agency in a Real-Scale City
Aug 27, 2026Tianjie Ju, Zheng Wu, Yueqing Sun +15Spatial Reasoning Benchmarks Robot Navigation
Shanghai Jiao Tong University · National University of Singapore · Meituan +3
OccPlanner: Goal-Aware Occupancy-Conditioned Diffusion Planner for PixelGoal Navigation
Aug 14, 2026Binling Huang, Nianjin Ye, Xi Yang +6Visual Navigation Trajectory Generation
Changhong Intelligent Robot University of Electronic Science and Technology of China
IoT-Enabled Autonomous Maritime Navigation in Smart Ports: A Curriculum-Guided Shared Policy Learning Framework
Aug 12, 2026Yuqing Lin, Rangya Zhang, Kum Fai YuenPartially Observable RL Robot Navigation
SAIN: Structure-Aware Interactive Navigation with Active Dialogue Grounding for Mobile Robot
Aug 10, 2026Yuhao Cao, Xiao Liu, Yang Xie +2Embodied Navigation Robot Navigation
School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, P.R. China · Department of Mechanical Engineering, City University of Hong Kong, Hong Kong SAR, China
LifelongCrossNav: Persistent 3D Semantic Memory for Cross-Floor Multi-Object Navigation
Aug 7, 2026Zehui Li, Zihao Sun, Jiawei Xu +6Embodied Navigation Robot Navigation
1Peking University · 2Beijing Academy of Artificial Intelligence
Unordered Landmark Visual Navigation
Aug 7, 2026Hao Ren, Junzhe Zhu, Yihan Li +8Visual Navigation Robot Navigation
Sun Yat-sen University, Guangzhou, China · Insta360 Research, Shenzhen, China
CrossTracer: Cross-Embodiment Navigation via VLA Model Reasoning and Trace Residuals Adapting
Aug 7, 2026Yao Wang, Siyuan Wang, Zhirui Sun +4Trajectory Generation Robot Navigation
Peng Cheng Laboratory · Southern University of Science and Technology · Innovation Investment Research Institute +1
Unified Planning-Learning Framework for Robust UUV Navigation Under Partial Observability
Aug 5, 2026Md Ether Deowan, Eleni KelasidiRL Control Partially Observable RL
Department of Mechanical and Industrial Engineering, Faculty of Engineering, NTNU, Trondheim, Norway.
Toward Integrating Adaptive Experience Replay and Online Uncertainty Estimation in Safe Actor-Critic Optimal Control
Aug 5, 2026Mahshad Rastegarmoghaddam, Davoud Nikkhouy, Shima SamadzadehRL Control Reinforcement Learning
Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy
A Vision-based Control Framework for Real-time Autonomous UUV Operations
Aug 5, 2026Erik Tjærand Frøland, Marco Job, Md Ether Deowan +1Robot Navigation Underwater 3D Reconstruction
Dept. of Mechanical and Industrial Engineering, NTNU, Norway · Oceaneering AS, Norway

Sep 15, 2026, cs.ROJ/K move · Enter open · S save

LEAP: Learning Emergent Active Perception for Quadruped Navigation

Ü. Bora Gökbakan, Stéphane Caron, Philippe Souères

WILLOW · Inria and DI ENS, PSL, Paris, France · ISIR+3

Robot Navigation Active View Selection Active Visual Perception

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Active perception allows autonomous agents to select their viewpoints rather than passively process the viewpoints given to them, enabling them to target where to reduce uncertainty about their environment. Learned systems typically encourage this behavior with hand-designed proxy objectives, such as coverage or curiosity bonuses, that may conflict with the task. In this work, we propose a method to learn emergent active perception (LEAP) without augmentation of the task objective. We formulate the problem of goal-oriented navigation over hazardous terrains with goals that must be discovered visually. We then propose an architecture for navigation policies with active perception, and train them on a terrain curriculum where task pressure alone leads to the emergence of gaze control. Key to this emergence, LEAP works on a gaze-invariant representation that integrates depth images into egocentric belief maps. We validate its performance in held-out evaluation scenarios, where it achieves a 92.7% success rate, compared to 74.2% for scripted or 34.5% for passive perception, and comes within 4.6 points of a privileged oracle. We validate that LEAP navigation policies, unchanged, can be directly applied to steering quadrupedal locomotion policies in physics simulation.

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