Researchers incorporate computer vision and uncertainty into AI for robotic prosthetics

Researchers have developed new software that can be integrated with existing hardware to enable people using robotic prosthetics or exoskeletons to walk in a safer, more natural manner on different types of terrain. The new framework incorporates computer vision into prosthetic leg control, and includes robust artificial intelligence (AI) algorithms that allow the software to better account for uncertainty. "Lower-limb robotic prosthetics need to execute different behaviors based on the terrain users are walking on," says Edgar Lobaton, co-author of a paper on the work and an associate professor of electrical and computer engineering at North Carolina State University. "The framework we've created allows the AI in robotic prostheses to predict the type of terrain users will be stepping on, quantify the uncertainties associated with that prediction, and then incorporate that uncertainty into its decision-making." The researchers focused on distinguishing between six different terrains that require adjustments in a robotic prosthetic's behavior: tile, brick, concrete, grass, "upstairs" and "downstairs."