AI tech to give independent control to robotic exoskeletons

The system being developed by robotics researchers at the University of Waterloo in Canada combines computer vision and deep-learning AI to mimic how able-bodied people walk by seeing their surroundings and adjusting their movements.

Sci-Fi Eye: the future of wearable exoskeletons

"We're giving robotic exoskeletons vision so they can control themselves," said Brokoslaw Laschowski, a PhD candidate in systems design engineering who is leading the ExoNet project at the university.

Motors are already employed in exoskeletons legs, but they have to be controlled manually by the user with smartphone applications or a joystick.

"That can be inconvenient and cognitively demanding," Laschowski said in a statement. "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 optimising AI computer software to process the video feed to accurately recognise 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.

"Our control approach wouldn't necessarily require human thought," said Laschowski, who is also a student member of the Waterloo Artificial Intelligence Institute (Waterloo.ai). "Similar to autonomous cars that drive themselves, we're designing autonomous exoskeletons and prosthetic legs that walk for themselves."

The researchers are also working to improve the energy efficiency of motors for robotic exoskeletons and prostheses by using human motion to self-charge the batteries.

The latest in a series of papers on the related projects, Simulation of Stand-to-Sit Biomechanics for Robotic Exoskeletons and Prostheses with Energy Regeneration, appears in IEEE Transactions on Medical Robotics and Bionics.