collaborators

14 papers

cs.RO2026

Deep Reinforcement Learning-Enhanced Event-Triggered Data-Driven Predictive Control for a 3D Cable-Driven Soft Robotic Arm

Cheng Ouyang, Moeen Ul Islam, Kaixiang Zhang +3

Soft robots are challenging to control due to their nonlinear and time-varying dynamics. Data-enabled predictive control (DeePC) offers a model-free alternative by directly leverag…

cs.RO2026

A Modular Dual-Arm Apple Harvesting Robot with Enhanced Field Performance

Keyi Zhu, Kyle Lammers, Chaaran Arunachalam +3

Robotic apple harvesting offers a promising solution to labor shortages in commercial orchards, but low throughput and poor performance in orchard environments hinder its commercia…

eess.SY2025

Learning-based data-enabled economic predictive control with convex optimization for nonlinear systems

Mingxue Yan, Xuewen Zhang, Kaixiang Zhang +2

In this article, we propose a data-enabled economic predictive control method for a class of nonlinear systems, which aims to optimize the economic operational performance while ha…

eess.SY2025

Distributed Platoon Control Under Quantization: Stability Analysis and Privacy Preservation

Kaixiang Zhang, Zhaojian Li, Wei Lin

Distributed control of connected and automated vehicles has attracted considerable interest for its potential to improve traffic efficiency and safety. However, such control scheme…

cs.RO2025

Velocity-Form Data-Enabled Predictive Control of Soft Robots under Unknown External Payloads

Huanqing Wang, Kaixiang Zhang, Kyungjoon Lee +5

Data-driven control methods such as data-enabled predictive control (DeePC) have shown strong potential in efficient control of soft robots without explicit parametric models. Howe…

cs.RO2025

Direct Data-Driven Predictive Control for a Three-dimensional Cable-Driven Soft Robotic Arm

Cheng Ouyang, Moeen Ul Islam, Dong Chen +3

Soft robots offer significant advantages in safety and adaptability, yet achieving precise and dynamic control remains a major challenge due to their inherently complex and nonline…