activity
20172020
most citedSelf-Powered Solar Aerial Vehicles: Towards Infinite Endurance UAVs

20 citations · 55 across the 9 of their papers we have counts for

collaborators

10 papers

cs.MA2020

Data-Driven Predictive Control Towards Multi-Agent Motion Planning With Non-Parametric Closed-Loop Behavior Learning

Jun Ma, Zilong Cheng, Wenxin Wang +3

In many specific scenarios, accurate and effective system identification is a commonly encountered challenge in the model predictive control (MPC) formulation. As a consequence, th…

math.OC2020★ 5 cited

Improved Hierarchical ADMM for Nonconvex Cooperative Distributed Model Predictive Control

Xiaoxue Zhang, Jun Ma, Zilong Cheng +3

Distributed optimization is often widely attempted and innovated as an attractive and preferred methodology to solve large-scale problems effectively in a localized and coordinated…

cs.RO2020

Mobile Robot Path Planning in Dynamic Environments: A Survey

Kuanqi Cai, Chaoqun Wang, Jiyu Cheng +2

There are many challenges for robot navigation in densely populated dynamic environments. This paper presents a survey of the path planning methods for robot navigation in dense en…

cs.CV2020★ 2 cited

Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment

Jing Wang, Jiahong Chen, Jianzhe Lin +2

In this study, we focus on the unsupervised domain adaptation problem where an approximate inference model is to be learned from a labeled data domain and expected to generalize we…

eess.SY2019★ 20 cited

Self-Powered Solar Aerial Vehicles: Towards Infinite Endurance UAVs

Farbod Khoshnoud, Ibrahim I. Esat, Clarence W. de Silva +3

A self-powered scheme is explored for achieving long-endurance operation, with the use of solar power and buoyancy lift. The end goal is the capability of infinite endurance while…

eess.SP2019★ 1 cited

Optimization of Wireless Sensor Network Deployment for Spatiotemporal Reconstruction and Prediction

Jiahong Chen, Teng Li, Jing Wang +1

This paper addresses the problem of optimizing sensor deployment locations to reconstruct and also predict a spatiotemporal field. A novel deep learning framework is developed to f…