Cornell researchers have developed a robotic feeding system that uses computer vision, machine learning and multimodal sensing to safely feed people with severe mobility limitations, including those with spinal cord injuries, cerebral palsy and multiple sclerosis.
A leader in assistive robotics, Bhattacharjee and his EmPRISE Lab have spent years teaching machines the complex process by which we humans feed ourselves. It's a complicated challenge to teach a machine -- everything from identifying food items on a plate, picking them up and then transferring it inside the mouth of a care recipient.
"Current technology only looks at a person's face once and assumes they will remain still, which is often not the case and can be very limiting for care recipients," said Rajat Kumar Jenamani, the paper's lead author and a doctoral student in the field of computer science. "This is one of the most extensive real-world evaluations of any autonomous robot-assisted feeding system with end-users," Bhattacharjee said.
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