4 papers
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…
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…
Human Motor Learning Dynamics in High-dimensional Tasks
Ankur Kamboj, Rajiv Ranganathan, Xiaobo Tan +1
Conventional approaches to enhancing movement coordination, such as providing instructions and visual feedback, are often inadequate in complex motor tasks with multiple degrees of…