34 citations · 39 across the 9 of their papers we have counts for
11 papers
EgoNeMo: Transferable Map of Pedestrian Dynamics via Egocentric LiDAR Scan
Azusa Sawada, Allan Wang, Hideo Saito +1
This paper proposes a transferable Map of Dynamics (MoD) framework that generalizes to unknown environments using only egocentric 3D LiDAR point clouds to overcome the long-standin…
LiDAR-based Crowd Navigation with Visible Edge Group Representation
Allan Wang, Aaron Steinfeld
Robot navigation in crowded pedestrian environments is a well-known challenge and we explore the practical deployment of group-based representations in this setting. Pedestrian gro…
HiCrowd: Hierarchical Crowd Flow Alignment for Dense Human Environments
Yufei Zhu, Shih-Min Yang, Martin Magnusson +1
Navigating through dense human crowds remains a significant challenge for mobile robots. A key issue is the freezing robot problem, where the robot struggles to find safe motions a…
EgoTraj-Bench: Towards Robust Trajectory Prediction Under Ego-view Noisy Observations
Jiayi Liu, Jiaming Zhou, Ke Ye +3
Reliable trajectory prediction from an ego-centric perspective is crucial for robotic navigation in human-centric environments. However, existing methods typically assume noiseless…
QuadKAN: KAN-Enhanced Quadruped Motion Control via End-to-End Reinforcement Learning
Yinuo Wang, Gavin Tao
We address vision-guided quadruped motion control with reinforcement learning (RL) and highlight the necessity of combining proprioception with vision for robust control. We propos…
TBD Pedestrian Data Collection: Towards Rich, Portable, and Large-Scale Natural Pedestrian Data
Allan Wang, Daisuke Sato, Yasser Corzo +3
Social navigation and pedestrian behavior research has shifted towards machine learning-based methods and converged on the topic of modeling inter-pedestrian interactions and pedes…