Researchers are developing exoskeleton legs capable of thinking and making control decisions on their own using sophisticated artificial intelligence (AI) technology. The ExoNet 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. Each time the user wants to perform a new locomotor activity, they have to stop, take out their 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 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. The control approach would not necessarily require human thought. Similar to autonomous cars that drive themselves, the autonomous exoskeletons would walk by themselves.
The researchers are also working to improve the energy efficiency of motors for robotic exoskeletons by using human motion to self-charge the batteries.