{"id":191,"date":"2025-07-08T08:18:00","date_gmt":"2025-07-08T12:18:00","guid":{"rendered":"https:\/\/carleton.ca\/mechatronics\/?page_id=191"},"modified":"2025-07-15T11:05:08","modified_gmt":"2025-07-15T15:05:08","slug":"exoskeleton","status":"publish","type":"page","link":"https:\/\/carleton.ca\/mechatronics\/exoskeleton\/","title":{"rendered":"Exoskeleton"},"content":{"rendered":"

Adaptive Exoskeleton Control using Deep Reinforcement Learning<\/h3>\n

Modern workplaces like warehouses and manufacturing facilities often involve repetitive and physically demanding tasks, leading to worker fatigue and injury. Powered exoskeletons offer a promising solution to augment human strength and endurance, but they often require complex, time-consuming calibration for each individual user. Our research aims to solve this problem by creating a truly “plug-and-play” elbow exoskeleton. We use advanced artificial intelligence, specifically deep reinforcement learning, to train a control system that learns to adapt to different users and tasks automatically. By training the controller in a highly realistic computer simulation across millions of randomized scenarios, it learns a robust strategy that transfers directly to the physical hardware. The final system uses non-invasive muscle sensors (sEMG) to understand the user’s intent and provides just the right amount of assistance in real-time, making the exoskeleton intuitive, effective, and ready to use without any manual tuning.<\/p>\n

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Adaptive Exoskeleton Control using Deep Reinforcement Learning Modern workplaces like warehouses and manufacturing facilities often involve repetitive and physically demanding tasks, leading to worker fatigue and injury. Powered exoskeletons offer a promising solution to augment human strength and endurance, but they often require complex, time-consuming calibration for each individual user. Our research aims to solve […]<\/p>\n","protected":false},"author":17,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":"","_links_to":"","_links_to_target":""},"yoast_head":"\nExoskeleton - Advanced Biomechatronics & Locomotion Lab<\/title>\n<meta name=\"description\" content=\"Adaptive Exoskeleton Control using Deep Reinforcement Learning Modern workplaces like warehouses and manufacturing facilities often involve repetitive and\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/carleton.ca\/mechatronics\/exoskeleton\/\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/carleton.ca\/mechatronics\/exoskeleton\/\",\"url\":\"https:\/\/carleton.ca\/mechatronics\/exoskeleton\/\",\"name\":\"Exoskeleton - 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