8 papers
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…
BiPneu: Design and Control of a Bipolar-Pressure Pneumatic System for Soft Robots
Yu Mei, Xinyu Zhou, Vedant Naik +2
Positive-negative pressure regulation is critical to soft robotic actuators, enabling large motion ranges and versatile actuation modes. However, achieving high-performance regulat…
Automated Curriculum Design for High-dimensional Human Motor Learning
Ankur Kamboj, Rajiv Ranganathan, Xiaobo Tan +1
Designing effective practice schedules for high-dimensional motor learning tasks remains a challenge, especially when skill states are unobservable and task performance may not ref…
Skill-informed Data-driven Haptic Nudges for High-dimensional Human Motor Learning
Ankur Kamboj, Rajiv Ranganathan, Xiaobo Tan +1
In this work, we propose a data-driven framework to design optimal haptic nudge feedback leveraging the learner's estimated skill to address the challenge of learning a novel motor…
AFT: Appearance-Based Feature Tracking for Markerless and Training-Free Shape Reconstruction of Soft Robots
Shangyuan Yuan, Preston Fairchild, Yu Mei +2
Accurate shape reconstruction is essential for precise control and reliable operation of soft robots. Compared to sensor-based approaches, vision-based methods offer advantages in…
Fast Online Adaptive Neural MPC via Meta-Learning
Yu Mei, Xinyu Zhou, Shuyang Yu +2
Data-driven model predictive control (MPC) has demonstrated significant potential for improving robot control performance in the presence of model uncertainties. However, existing…