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…
Co-Learning Port-Hamiltonian Systems and Optimal Energy-Shaping Control
Ankur Kamboj, Biswadip Dey, Vaibhav Srivastava
We develop a physics-informed learning framework for energy-shaping control of port-Hamiltonian (pH) systems from trajectory data. The proposed approach co-learns a pH system model…
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…
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…