activity
20172026
most citedLifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems

260 citations · 512 across the 34 of their papers we have counts for

collaborators
Showing 2022Show all

8 papers · 1 filter

cs.RO2022★ 14 cited

Efficient Speed Planning for Autonomous Driving in Dynamic Environment with Interaction Point Model

Yingbing Chen, Ren Xin, Jie Cheng +4

Safely interacting with other traffic participants is one of the core requirements for autonomous driving, especially in intersections and occlusions. Most existing approaches are…

cs.CV2022★ 2 cited

RNGDet++: Road Network Graph Detection by Transformer with Instance Segmentation and Multi-scale Features Enhancement

Zhenhua Xu, Yuxuan Liu, Yuxiang Sun +2

The road network graph is a critical component for downstream tasks in autonomous driving, such as global route planning and navigation. In the past years, road network graphs are…

cs.CV2022

CenterLineDet: CenterLine Graph Detection for Road Lanes with Vehicle-mounted Sensors by Transformer for HD Map Generation

Zhenhua Xu, Yuxuan Liu, Yuxiang Sun +2

With the fast development of autonomous driving technologies, there is an increasing demand for high-definition (HD) maps, which provide reliable and robust prior information about…

cs.RO2022★ 3 cited

ElasticROS: An Elastically Collaborative Robot Operation System for Fog and Cloud Robotics

Boyi Liu

Robots are integrating more huge-size models to enrich functions and improve accuracy, which leads to out-of-control computing pressure. And thus robots are encountering bottleneck…

cs.RO2022★ 1 cited

FusionPortable: A Multi-Sensor Campus-Scene Dataset for Evaluation of Localization and Mapping Accuracy on Diverse Platforms

Jianhao Jiao, Hexiang Wei, Tianshuai Hu +10

Combining multiple sensors enables a robot to maximize its perceptual awareness of environments and enhance its robustness to external disturbance, crucial to robotic navigation. T…

cs.CV2022★ 1 cited

MMFN: Multi-Modal-Fusion-Net for End-to-End Driving

Qingwen Zhang, Mingkai Tang, Ruoyu Geng +3

Inspired by the fact that humans use diverse sensory organs to perceive the world, sensors with different modalities are deployed in end-to-end driving to obtain the global context…