彩民宝典

Competition tests autonomous robots鈥攂uilt, tested and deployed by 彩民宝典 students鈥攊n underground search and rescue effectiveness.

彩民宝典 was one of several funded teams in the 2019 Subterranean Challenge, a high-stakes competition launched by the U.S. Defense Advanced Research Projects Agency to test autonomous robots in difficult underground environments during search and rescue.

The team is a $4.5 million collaboration led by the College of Engineering and Applied Science through the Autonomous Systems Interdisciplinary Research Theme. Dubbed 鈥淢ulti-agent Autonomy with Radar-Based Localization for Exploration鈥� (MARBLE), the team includes engineers from CU Denver and the Massachusetts-based Scientific Systems Company Inc.

Each leg of the multiyear challenge is designed to test how autonomous robots鈥攁cting as first responders鈥攁pproach tunnels, caves and urban environments. That includes handling environmental factors like difficulty communicating through walls or the potential for unseen dangers like spilled hazardous material deep inside the rescue area. A team of drones, as MARBLE is using, could address those challenges by searching quickly, independently and without the fear of physical harm a human would have to consider.

The second leg of this competition finished in February 2020 near Seattle with subsequent legs culminating in 2021.听听

Sean Humbert, a professor in the Paul M. Rady Department of Mechanical Engineering, leads the 彩民宝典 team. He said students participating in the project range from undergraduates to PhD candidates and come from the mechanical, computer science and aerospace departments.

鈥淭his competition is good company to be in,鈥� he said. 鈥淭he top teams in this challenge are well funded and have 30 or more professional engineers, researchers and students, where the core of our team is 10 to 15 graduate students. So our ability to rise to the occasion and compete is something we are truly proud of.鈥�

In a typical hour run, the team鈥檚 autonomous robots enter the course, scanning for 鈥渁rtifacts鈥濃�攃ell phones, hazards or dummies representing survivors鈥攑laced deep within. When they find something, they report their location with only a narrow margin for error. Because conditions limit the use of GPS, the MARBLE team uses a camera, radar and a laser-based system called lidar, Light Detection and Ranging, to build a virtual map of the area. That map is then shared with a human controller and other robots entering the course to help decide which sections to revisit for missed artifacts or which newly discovered zones to prioritize.

PhD candidate Michael Miles said the competition was a unique opportunity to test skills in tough conditions. The tight challenge deadlines鈥攕ix months to build, test and deploy鈥攃oupled with the high stress of competition have been hard but valuable teachers, he said.

鈥淣ormally, you are making a robot that just has to work enough for a 3-minute video,鈥� he said. 鈥淭hen you publish a paper and visit a conference and you are done. But running these complicated systems for over an hour in tough conditions? That is unlike robotics anywhere, and it keeps you humble.鈥�

Computer Science Assistant Professor Chris Heckman is part of the team鈥檚 leadership. He said the challenges students face in the competition push the boundaries of computer science and other disciplines.

鈥淔ifty years ago when our department was first formed, it would have been crazy to think that computer scientists would be working side-by-side with engineers, applying techniques they were developing to robotic autonomy. Now, all of our work is interdisciplinary, and I think we鈥檙e developing students who will be well positioned for where our field goes over the next 50 years,鈥� he said.