University of Waterloo researchers are using deep learning and computer vision to develop autonomous exoskeleton legs to help users walk, climb stairs, and avoid obstacles. The ExoNet project, described in an early-access paper on "Frontiers in Robotics and AI", fits users with wearable cameras. AI software processes the camera's video stream, and is being trained to recognize surrounding features such as stairs and doorways, and then determine the best movements to take. "Our control approach wouldn't necessarily require human thought," said Brokoslaw Laschowski, Ph.D. candidate in systems design engineering and lead author on the ExoNet project. "Similar to autonomous cars that drive themselves, we're designing autonomous exoskeletons that walk for themselves."
Increased Integration of Different Solutions to Provide Improved Performance 184.108.40.206 Rapid Industrial Growth in Emerging Economies 5.2.4 Challenges 220.127.116.11 Threats Related to Cybersecurity 18.104.22.168 Complexity in Implementation of Smart Manufacturing Technology Systems 22.214.171.124 Lack of Awareness About Benefits of Adopting Information and Enabling Technologies 126.96.36.199 Lack of Skilled Workforce 5.3 Industrial Wearable Devices Trends in Smart Manufacturing 5.3.1 By Device 188.8.131.52