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20232026
most citedBack-stepping Experience Replay with Application to Model-free Reinforcement Learning for a Soft Snake Robot

11 citations · 20 across the 8 of their papers we have counts for

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7 papers · 1 filter

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 Novel Modular Cable-Driven Soft Robotic Arm with Multi-Segment Reconfigurability

Moeen Ul Islam, Cheng Ouyang, Xinda Qi +3

This paper presents a novel, modular, cable-driven soft robotic arm featuring multi-segment reconfigurability. The proposed architecture enables a stackable system with independent…

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…

cs.RO2025

DiSA-IQL: Offline Reinforcement Learning for Robust Soft Robot Control under Distribution Shifts

Linjin He, Xinda Qi, Dong Chen +2

Soft snake robots offer remarkable flexibility and adaptability in complex environments, yet their control remains challenging due to highly nonlinear dynamics. Existing model-base…

cs.RO2024★ 11 cited

Back-stepping Experience Replay with Application to Model-free Reinforcement Learning for a Soft Snake Robot

Xinda Qi, Dong Chen, Zhaojian Li +1

In this paper, we propose a novel technique, Back-stepping Experience Replay (BER), that is compatible with arbitrary off-policy reinforcement learning (RL) algorithms. BER aims to…

cs.RO2024

Design and Nonlinear Modeling of a Modular Cable Driven Soft Robotic Arm

Xinda Qi, Yu Mei, Dong Chen +2

We propose a novel multi-section cable-driven soft robotic arm inspired by octopus tentacles along with a new modeling approach. Each section of the modular manipulator is made of…

cs.RO2023★ 7 cited

Multi-Agent Reinforcement Learning for Connected and Automated Vehicles Control: Recent Advancements and Future Prospects

Min Hua, Dong Chen, Xinda Qi +4

Connected and automated vehicles (CAVs) are considered a potential solution for future transportation challenges, aiming to develop systems that are efficient, safe, and environmen…