activity
20202026
most citedLearning World Transition Model for Socially Aware Robot Navigation

5 citations · 5 across the 9 of their papers we have counts for

collaborators
Showing cs.ROShow all

8 papers · 1 filter

cs.RO2026

Revisiting Topological Graphs for Macro Action based Closed-loop Reinforcement Learning of Vision Language Navigation in Continuous Environment

Shuhao Ye, Sitong Mao, Yuxiang Cui +7

Vision-Language Navigation in Continuous Environments (VLN-CE) requires an agent to follow natural language instructions through unseen environments. Existing imitation learning (I…

cs.RO2026

Embodied-Navigator: Point, Think, Memorize, and Align for Efficient Navigation

Hongyan Feng, Sunlai Chen, Xuanyu Liu +9

Although Large Vision-Language Models (VLMs) have significantly advanced embodied navigation, their direct deployment remains challenging, as existing methods often force VLMs into…

cs.RO2025

ETP-R1: Evolving Topological Planning with Reinforcement Fine-tuning for Vision-Language Navigation in Continuous Environments

Shuhao Ye, Sitong Mao, Yuxiang Cui +6

Vision-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to navigate towards target in continuous environments, following natural language instruct…

cs.RO2025

BEV-ODOM2: Enhanced BEV-based Monocular Visual Odometry with PV-BEV Fusion and Dense Flow Supervision for Ground Robots

Yufei Wei, Chenxiao Hu, Wangtao Lu +5

Scale-consistent ego-motion estimation is fundamental for autonomous ground robots. Bird's-Eye-View (BEV) representation naturally addresses the scale drift problem of monocular vi…

cs.RO2023

Zero-shot Transfer Learning of Driving Policy via Socially Adversarial Traffic Flow

Dongkun Zhang, Jintao Xue, Yuxiang Cui +6

Acquiring driving policies that can transfer to unseen environments is challenging when driving in dense traffic flows. The design of traffic flow is essential and previous studies…

cs.RO2021

Learning Observation-Based Certifiable Safe Policy for Decentralized Multi-Robot Navigation

Yuxiang Cui, Longzhong Lin, Xiaolong Huang +3

Safety is of great importance in multi-robot navigation problems. In this paper, we propose a control barrier function (CBF) based optimizer that ensures robot safety with both hig…