5 citations · 10 across the 7 of their papers we have counts for
7 papers
Learning-Accelerated Optimization-based Trajectory Planning for Cooperative Aerial-Ground Handover Missions
Jingshan Chen, Bochen Yu, Henrik Ebel +1
This paper presents a learning-augmented trajectory planning framework for cooperative unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) handover missions. While cent…
Model Predictive Path-Following Control for a Quadrotor
David Leprich, Mario Rosenfelder, Mario Hermle +2
Automating drone-assisted processes is a complex task. Many solutions rely on trajectory generation and tracking, whereas in contrast, path-following control is a particularly prom…
An Online Optimization-Based Trajectory Planning Approach for Cooperative Landing Tasks
Jingshan Chen, Lihan Xu, Henrik Ebel +1
This paper presents a real-time trajectory planning scheme for a heterogeneous multi-robot system (consisting of a quadrotor and a ground mobile robot) for a cooperative landing ta…
Time-Optimal Handover Trajectory Planning for Aerial Manipulators based on Discrete Mechanics and Complementarity Constraints
Wei Luo, Jingshan Chen, Henrik Ebel +1
Planning a time-optimal trajectory for aerial robots is critical in many drone applications, such as rescue missions and package delivery, which have been widely researched in rece…
Who is next: rising star prediction via diffusion of user interest in social networks
Xuan Yang, Yang Yang, Jintao Su +5
Finding items with potential to increase sales is of great importance in online market. In this paper, we propose to study this novel and practical problem: rising star prediction.…
Partially latent factors based multi-view subspace learning
Run-kun Lu, Jian-wei Liu, Ze-yu Liu +1
Multi-view subspace clustering always performs well in high-dimensional data analysis, but is sensitive to the quality of data representation. To this end, a two stage fusion strat…
Exploiting Behavioral Consistence for Universal User Representation
Jie Gu, Feng Wang, Qinghui Sun +4
User modeling is critical for developing personalized services in industry. A common way for user modeling is to learn user representations that can be distinguished by their inter…