HUMAN AND MACHINE LEARNING FOR CUSTOMIZED CONTROL OF ASSISTIVE ROBOTS

PROJECT SUMMARY This application will result in a technological platform that re-empowers persons with severe paralysis, by allowing them to independently control a wide spectrum of robotic actions. Severe paralysis is devastating, and chronic—and reliance on caregivers is persistent. Assistive machines such as wheelchairs and robotic arms offer a groundbreaking path to independence: where control over their environment and interactions is returned to the person. However, to operate complex machines like robotic arms and hands typically poses a difficult learning challenge and requires complex control signals—and the commercial control interfaces accessible to persons with severe paralysis (e.g. sip-and-puff, switch-based head arrays) are not adequate. As a result, assistive robotic arms remain largely inaccessible to those with severe paralysis—arguably the population who would benefit from them most.

CAREER: ROBOT LEARNING FROM MOTOR-IMPAIRED INSTRUCTORS AND TASK PARTNERS

CPS: SYNERGY: COLLABORATIVE RESEARCH: LEARNING CONTROL SHARING STRATEGIES FOR ASSISTIVE CYBER-PHYSICAL SYSTEMS