Using sophisticated artificial intelligence (AI) technology, newly developed exoskeleton legs capable of thinking and making control decisions on their own. The system combines computer vision and deep-learning AI to mimic how able-bodied people walk by seeing their surroundings and adjusting their movements.
Exoskeleton legs operated by motors already exist, but they must be manually controlled by users via smartphone applications or joysticks.
“That can be inconvenient and cognitively demanding,” says Brokoslaw Laschowski, a PhD candidate in systems design engineering who leads a University of Waterloo research project called ExoNet. “Every time you want to perform a new locomotor activity, you have to stop, take out your smartphone and select the desired mode.”
To address that limitation, the researchers fitted exoskeleton users with wearable cameras and are now optimizing AI computer software to process the video feed to accurately recognize stairs, doors and other features of the surrounding environment.
The next phase of the ExoNet research project will involve sending instructions to motors so that robotic exoskeletons can climb stairs, avoid obstacles or take other appropriate actions based on analysis of the user’s current movement and the upcoming terrain.