Quadruped Robot Navigation

Latest papers

21 papers8 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

DR-VLA: Learning Human-Like Quadruped Navigation from Egocentric Web Videos via Domain-Invariant Scene Representations
Oct 13, 2026Jun Tian, Yingjie Niu, Ruo Chen +2Quadruped Robot Navigation Robot Navigation
Deep Robotics · University of Illinois at Urbana-Champaign · Zhejiang University +2
PointWalker: Mapless Quadruped Locomotion Directly From Raw LiDAR Point Clouds
Oct 11, 2026Sicen Li, Zhen Chu, Chao Li +3Quadruped Locomotion Legged Robotics
College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China · Yunshenchu Technology Co., Ltd., Hangzhou, China · Hangzhou Public Library, Hangzhou, China +1
Load-Aware Quadruped Navigation with Online Contact-based Geometry Estimation
Oct 10, 2026Qi Yin, XiaoLi Zhang, Yangming ShiRobot Navigation Quadruped Robot Navigation
Colorado School of Mines, Golden, CO 80401, USA
CMP-IRRT*: A Perception-Assisted Height-Adaptive Planner for Quadruped Robots
Oct 7, 2026Mingfan Zhao, Wendong Mao, Zhongfeng WangQuadruped Robot Navigation Robot Navigation
School of Integrated Circuits, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
TACET: Context-Appropriate Acoustic-Social Navigation for Quadrupeds
Oct 2, 2026Sungsan Park, Young-Sik Shin, Sanghyun KimRobot Navigation Social Robot Navigation
Department of Mechanical Engineering, Kyung Hee University, Yongin, 17104, Republic of Korea. · School of Mechanical Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea.
Experience-Driven Continual Learning of Terrain Traversability for Quadruped Robots
Sep 30, 2026Luca Bricarello, João Carlos Virgolino Soares, Alberto Sanchez-Delgado +2Continual Robot Learning Safe Robot Navigation
Dynamic Legged Systems Lab, Istituto Italiano di Tecnologia, Genoa, Italy. · Universit`a degli Studi di Genova, Genoa, Italy.
FutureRay: Control-Aligned Future Range for Agile Quadruped Navigation
Sep 26, 2026Tianhao Zang, Shanze Wang, Ziqian Wang +4Robot Navigation Safe Robot Navigation
College of Information Science and Technology, Eastern Institute of Technology, Ningbo, P. R. China. · University of Maryland, USA. · The Hong Kong Polytechnic University, Hong Kong. +2
Taming an End-to-End Autonomous Driving Policy for Urban Navigation of Quadruped Robots
Sep 23, 2026Joochan Kim, Chanuk Yang, Tackgeun You +2Robot Navigation Quadruped Robot Navigation
Purdue University · Korea Institute of Science and Technology (KIST)
LEAP: Learning Emergent Active Perception for Quadruped Navigation
Sep 15, 2026Ü. Bora Gökbakan, Stéphane Caron, Philippe SouèresRobot Navigation Quadruped Robot Navigation
WILLOW · ISIR · LAAS-GEPETTO
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
DELTA: Deformable Elevation-Based Local Terrain Attention Encoder for Sparse-Terrain Quadrupedal Locomotion
Aug 22, 2026Sanghyun Park, Moonkyu Jung, Jemin HwangboTerrain-Aware Robot Locomotion Robot Locomotion
Robotics and Artificial Intelligence Lab, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon 34141, Republic of Korea
Learning Agile Navigation in Crowded Environments for Quadruped Robots
Jul 16, 2026Shuyu Wu, Zeyu Liu, Tianbao Zhang +6Robot Policy Learning Robot Navigation
Shanghai Jiao Tong University, Shanghai 200240, China · State Key Laboratory of High-end Heavy-load Robots, Midea Group, Foshan 528300, China
Stop to Decide: Latency-Aware Proprioceptive Navigation Primitives for Mapping-Free Quadruped Inspection
Jul 13, 2026Hanting Suo, Haonan Yan, Liang Wang +1Robotic Control Robot Navigation
School of Instrument Science and Engineering, Southeast University, Nanjing, China. · School of Electrical Engineering, Southeast University, Nanjing, China. · School of Mechanical Engineering, Southeast University, Nanjing, China.
SCAN-Planner: Spatial Collision-Aware Local Planning for Route-Guided Long-Range Quadruped Navigation
Jun 17, 2026Han Zheng, Zhe Chen, Yiwen Fu +2Collision Avoidance Robot Navigation
Shanghai Jiao Tong University, Shanghai, China.
Robot Squid Game: Quadrupedal Locomotion for Traversing Narrow Tunnels
May 13, 2026Amir Hossain Raj, Dibyendu Das, Xuesu XiaoLegged Robotics RL for Legged Locomotion
Department of Computer Science, George Mason University
HiPAN: Hierarchical Posture-Adaptive Navigation for Quadruped Robots in Unstructured 3D Environments
Apr 29, 2026Jeil Jeong, Minsung Yoon, Seokryun Choi +3Robot Navigation Quadruped Robot Navigation
School of Computing, KAIST, South Korea.
SmoothTurn: Learning to Turn Smoothly for Agile Navigation with Quadrupedal Robots
Mar 13, 2026Zunzhi You, Yunke Wang, Haolan Guo +1Robot Policy Learning Robot Navigation
School of Computer Science, University of Sydney
SEA-Nav: Efficient Policy Learning for Safe and Agile Quadruped Navigation in Cluttered Environments
Mar 10, 2026Shiyi Chen, Mingye Yang, Haiyi Liu +6Quadruped Robot Navigation Robot Navigation
Tsinghua University, Beijing, China. · Imperial College London, London, UK.
Task-Level Decisions to Gait Level Control: A Hierarchical Policy Approach for Quadruped Navigation
Mar 6, 2026Sijia Li, Haoyu Wang, Shenghai Yuan +2Quadruped Robot Navigation Robot Navigation
Efficient Autonomous Navigation of a Quadruped Robot in Underground Mines on Edge Hardware
Mar 4, 2026Yixiang Gao, Kwame Awuah-OffeiQuadruped Robot Navigation Robot Navigation
Department of Mining and Explosive Engineering, Missouri University of Science and Technology, Rolla, USA
TRAIN: Terrain-Aware Interactive Navigation for Quadruped Robots via Reinforcement Learning
Feb 13, 2026Wei Zhu, Irfan Tito Kurniawan, Ye Zhao +1Quadruped Robot Navigation Terrain-Aware Robot Locomotion
Department of Robotics, Graduate School of Engineering, Tohoku University, 980-8579, Sendai, Japan. · Laboratory for Intelligent Decision and Autonomous Robots, Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30313, USA.

Oct 13, 2026J/K move · Enter open · S save

DR-VLA: Learning Human-Like Quadruped Navigation from Egocentric Web Videos via Domain-Invariant Scene Representations

Jun Tian, Yingjie Niu, Ruo Chen, Hongyi Lin+1

Deep Robotics · University of Illinois at Urbana-Champaign · Zhejiang University+2

Quadruped Robot Navigation Robot Navigation Cross-Embodiment Robot Learning VLMs for Robotics Data-Efficient Robot Learning World Models for Robotics+1

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Quadruped robots performing outdoor deliveries must interpret complex scenes, anticipate changes, and navigate in socially compliant ways. Robot demonstrations are costly to collect at the scale needed for generalization. Egocentric web videos offer abundant human navigation experience, but differences in viewpoint and motion make this experience difficult to transfer to robots. We introduce DR-VLA, a Mixture-of-Transformers framework that transfers human navigation experience through a domain-invariant scene representation (DISR). The framework combines vision-language understanding and latent world modeling with a flow-matching action expert. We introduce EgoLynx, comprising 10,000 hours of curated egocentric web video (EgoLynx-Web) and 2,000 clips of teleoperated robot navigation collected during real-world deliveries (EgoLynx-Robot). We pretrain the understanding and world experts on EgoLynx-Web without action labels, then adapt the model to robot observations and train the action expert on EgoLynx-Robot to predict executable trajectories. We also propose the Quadruped Navigation Score (QNS), a pseudo-closed-loop metric combining safety, instruction compliance, comfort, and progress. On the held-out EgoLynx-Robot test split, DR-VLA improves QNS by approximately 5% and reduces open-loop final heading error (FHE) by 14.6%, each relative to the best competing result for that metric. Ablations show that web-video pretraining improves generalization and that the model's key components contribute to performance. As a future-prediction target, DISR outperforms five generic visual representations and yields performance close to task-specific 3D perception without dedicated geometric labels or point clouds for target construction. Trained separately on NAVSIM v1 without web pretraining, DR-VLA achieves 92.1 PDMS, suggesting that the framework also applies to autonomous driving.