2 citations · 6 across the 6 of their papers we have counts for
8 papers
Incremental Few-Shot Learning via Implanting and Compressing
Yiting Li, Haiyue Zhu, Xijia Feng +5
This work focuses on tackling the challenging but realistic visual task of Incremental Few-Shot Learning (IFSL), which requires a model to continually learn novel classes from only…
Velocity Obstacle Based Risk-Bounded Motion Planning for Stochastic Multi-Agent Systems
Xiaoxue Zhang, Jun Ma, Zilong Cheng +2
In this paper, we present an innovative risk-bounded motion planning methodology for stochastic multi-agent systems. For this methodology, the disturbance, noise, and model uncerta…
Receding Horizon Motion Planning for Multi-Agent Systems: A Velocity Obstacle Based Probabilistic Method
Xiaoxue Zhang, Jun Ma, Zilong Cheng +2
In this paper, a novel and innovative methodology for feasible motion planning in the multi-agent system is developed. On the basis of velocity obstacles characteristics, the chanc…
Generalized Iterative Super-Twisting Sliding Mode Control: A Case Study on Flexure-Joint Dual-Drive H-Gantry Stage
Wenxin Wang, Jun Ma, Zilong Cheng +3
Mechatronic systems are commonly used in the industry, where fast and accurate motion performance is always required to guarantee manufacturing precision and efficiency. Neverthele…
Semi-Definite Relaxation Based ADMM for Cooperative Planning and Control of Connected Autonomous Vehicles
Xiaoxue Zhang, Zilong Cheng, Jun Ma +3
This paper investigates the cooperative planning and control problem for multiple connected autonomous vehicles (CAVs) in different scenarios. In the existing literature, most of t…
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…