My research on the synergy of human and robotic systems aims to develop motion and task planning strategies for wearable and humanoid robots, based on the behavior and preference demonstrated in human motion coordination and task plans. For wearable robots such as the upper limb exoskeletons for stroke rehabilitation, the arm posture of the robots cannot be appropriately determined using the general kinematic redundancy resolution methods for manipulation robots, yet it can be accurately predicted based on human perception-action coordination. Such bio-inspired motion planning is applicable not only to the wearable robots with human-compatible physical structures, but to robots that are quite different from human in embodiment. For instance, the coordination of surgical robot arm with tool tips, as well as the complex motion coordination of a mobile humanoid robots, can be both be inspired by the macro- and micro-structure coordination and perception-action coordination revealed in human motion control.
At WPI, my research focuses on the shared-autonomous control of tele-nursing robots. My projects on shared autonomous perception-action coordination and fatigue-adaptive teleoperation interface investigate how the understanding of human behavior and preference in various motion coordinations can be used to design a better human-robot teaming that that reduce human operator’s cognitive and physical efforts. I also develop high-fidelity computational human model, for accurate performance assessment and behavior prediction in human-robot interaction.