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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

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Showing 2019Show all

6 papers · 1 filter

cs.RO2019★ 2 cited

Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Data

Boyi Liu, Lujia Wang, Ming Liu +1

Humans are capable of learning a new behavior by observing others to perform the skill. Similarly, robots can also implement this by imitation learning. Furthermore, if with extern…

cs.CV2019

A Robust Stereo Camera Localization Method with Prior LiDAR Map Constrains

Dong Han, Zuhao Zou, Lujia Wang +1

In complex environments, low-cost and robust localization is a challenging problem. For example, in a GPSdenied environment, LiDAR can provide accurate position information, but th…

cs.RO2019★ 4 cited

Federated Imitation Learning: A Privacy Considered Imitation Learning Framework for Cloud Robotic Systems with Heterogeneous Sensor Data

Boyi Liu, Lujia Wang, Ming Liu +1

Humans are capable of learning a new behavior by observing others perform the skill. Robots can also implement this by imitation learning. Furthermore, if with external guidance, h…

cs.RO2019

A Robust Roll Angle Estimation Algorithm Based on Gradient Descent

Rui Fan, Lujia Wang, Ming Liu +1

This paper presents a robust roll angle estimation algorithm, which is developed from our previously published work, where the roll angle was estimated from a dense disparity map b…

cs.CV2019★ 4 cited

A Novel Dual-Lidar Calibration Algorithm Using Planar Surfaces

Jianhao Jiao, Qinghai Liao, Yilong Zhu +5

Multiple lidars are prevalently used on mobile vehicles for rendering a broad view to enhance the performance of localization and perception systems. However, precise calibration o…

cs.RO2019★ 260 cited

Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems

Boyi Liu, Lujia Wang, Ming Liu

This paper was motivated by the problem of how to make robots fuse and transfer their experience so that they can effectively use prior knowledge and quickly adapt to new environme…