How do we interact with our environment so delicately? I want to understand what the neural processes are behind our movements. I take a robotic/control view on this; after all, some information is processed and a signal is generated (motor neurons fired) to command the mechanical actuators (muscles) to move the links (bones). Can we replicate similar control processes in robots?
For an updated list of my publications, please see my Google Scholar page.
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Bridging motor control and biomechanics
How do humans control a complex object? Optimal control is a leading theory in human sensorimotor neuroscience. But existing formulations often ignore the biomechanics of the body as a major contributor to the overall task dynamics. My work seeks to explain how the innate mechanics of the body and the information-processing centers in the brain share control responsibility in producing and maintaining movement.
Human-aware control of robots
Current state-of-the-art bio-robots (e.g., assistive exoskeletons or rehabilitation robots) are hard-coded to perform specific actions after detecting the user’s intent. This control paradigm is inherently limiting, as humans inevitably adapt their behavior in response to the interaction with the robot in the short and long timescales. Our current robots are unaware of the ever-changing biological states of the user.
In my human-aware robotic platform, a mathematical model of the human neuromuscular control is embedded in the robot’s controller—robots can infer the user’s behavior, capabilities, and limitations, to accordingly respond, adapt, correct, or assist. This brings a paradigm shift in how we design and control bio-robots.
Biomimetic movement controllers for in-vitro simulations
The human hand is a complex biomechanical system. Here is the conundrum: to study human hands, we need accurate mathematical models, and to make accurate models we need a better understanding of its biomechanics. A promising way out is in-vitro simulation. A robotic in-vitro hand simulator can give valuable insight into the biomechanical of the hand. For higher reliability of the results, the artificial movement controller must be as close to our neural controller as possible. I designed a multi-degree-of-freedom hand simulator with a biomimetic controller that created multi-joint movements with high repeatability and reliability.