152 citations · 179 across the 9 of their papers we have counts for
9 papers
Semantic2D: Enabling Semantic Scene Understanding with 2D Lidar Alone
Zhanteng Xie, Yipeng Pan, Yinqiang Zhang +2
This article presents a complete semantic scene understanding workflow using only a single 2D lidar. This fills the gap in 2D lidar semantic segmentation, thereby enabling the reth…
SCOPE: Stochastic Cartographic Occupancy Prediction Engine for Uncertainty-Aware Dynamic Navigation
Zhanteng Xie, Philip Dames
This article presents a family of Stochastic Cartographic Occupancy Prediction Engines (SCOPEs) that enable mobile robots to predict the future states of complex dynamic environmen…
Towards Predicting Collective Performance in Multi-Robot Teams
Pujie Xin, Zhanteng Xie, Philip Dames
The increased deployment of multi-robot systems (MRS) in various fields has led to the need for analysis of system-level performance. However, creating consistent metrics for MRS i…
Distributed Multi-Robot Multi-Target Tracking Using Heterogeneous Limited-Range Sensors
Jun Chen, Mohammed Abugurain, Philip Dames +1
This paper presents a cooperative multi-robot multi-target tracking framework aimed at enhancing the efficiency of the heterogeneous sensor network and, consequently, improving ove…
DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles
Zhanteng Xie, Philip Dames
This paper proposes a novel learning-based control policy with strong generalizability to new environments that enables a mobile robot to navigate autonomously through spaces fille…
Stochastic Occupancy Grid Map Prediction in Dynamic Scenes
Zhanteng Xie, Philip Dames
This paper presents two variations of a novel stochastic prediction algorithm that enables mobile robots to accurately and robustly predict the future state of complex dynamic scen…