36 citations · 60 across the 14 of their papers we have counts for
6 papers · 1 filter
DPed-VLN: A Benchmark for Socially Compliant Vision-and-Language Navigation in Dynamic Pedestrian Environments
Haojie Dai, Xiangyi Wang, Liuyi Wang +5
Vision-and-language navigation (VLN) has advanced rapidly in static indoor environments, but robots operating in human-populated spaces must ground language while responding to mov…
A Comprehensive Survey and Systematic Real-World Evaluation of Embodied Vision-and-Language Navigation
Liuyi Wang, Kai Sheng, Zongtao He +8
Navigation is a fundamental capability of autonomous systems, yet most existing approaches rely on highly structured models and strong prior assumptions, limiting their robustness…
KinematicRL: A Sim-to-Real Reinforcement Learning Framework For Social Navigation With Kinodynamic Feasibility
Zhiming Xu, Haodong Yang, Chengju Liu +2
Deep Reinforcement Learning (DRL) has shown promise for social navigation, yet its real-world deployment remains hindered by a persistent sim-to-real gap arising from simplified fi…
Dynamics Are Learned, Not Told: Semi-Supervised Discovery of Latent Dynamics Geometries For Zero-Shot Policy Adaptation
Zhiming Xu, Weitao Zhou, Xianghui Pan +4
Real-world dynamics shifts pose a critical challenge for reinforcement learning in robotics, as policies tightly coupled to nominal environments often fail catastrophically when ph…
Online,Target-Free LiDAR-Camera Extrinsic Calibration via Cross-Modal Mask Matching
Zhiwei Huang, Yikang Zhang, Qijun Chen +1
LiDAR-camera extrinsic calibration (LCEC) is crucial for data fusion in intelligent vehicles. Offline, target-based approaches have long been the preferred choice in this field. Ho…
Three-Filters-to-Normal+: Revisiting Discontinuity Discrimination in Depth-to-Normal Translation
Jingwei Yang, Bohuan Xue, Yi Feng +3
This article introduces three-filters-to-normal+ (3F2N+), an extension of our previous work three-filters-to-normal (3F2N), with a specific focus on incorporating discontinuity dis…