Robotic prosthetics master more natural movement on different terrains

The new framework is said to incorporate computer vision into prosthetic leg control and includes artificial intelligence (AI) algorithms that allows new software to better account for uncertainty.

Engineering can take inspiration from nature for better prosthetics

"Lower-limb robotic prosthetics need to execute different behaviours based on the terrain users are walking on," said Edgar Lobaton, co-author of a paper on the work and an associate professor of electrical and computer engineering at North Carolina State University (NC State). "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 behaviour, namely tile, brick, concrete, grass, ‘upstairs’ and ‘downstairs.’

"If the degree of uncertainty is too high, the AI isn't forced to make a questionable decision - it could instead notify the user that it doesn't have enough confidence in its prediction to act, or it could default to a 'safe' mode," said Boxuan Zhong, lead author of the paper and a recent Ph.D. graduate from NC State.