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One thousand feet underground, a four-legged creature scavenges through tunnels in pitch darkness. With vision that cuts through the blackness, it explores a spider web of paths, remembering its every step and navigating with precision. The sound of its movements echo eerily off the walls, but it is not to be feared – this is no wild animal; it is an autonomous rescue robot.

Initially designed to find survivors in collapsed mines, caves, and damaged buildings, that is only part of what it can do.

Created by a team of �鶹ӰԺ researchers and students, the robots placed third as the top US entry and earned $500,000 in prize money at a Defense Advanced Projects Research Agency Subterranean Challenge competition in 2021.

Going Futher

Two years later, they are pushing the technology even further, earning new research grants to expand the technology and create new applications in the rapidly growing world of autonomous systems.

“Ideally you don’t want to put humans in harm’s way in disaster situations like mines or buildings after earthquakes; the walls or ceilings could collapse and maybe some already have,” said Sean Humbert, a professor of mechanical engineering and director of the Robotics Program at CU �鶹ӰԺ. “These robots can be disposable while still providing situational awareness.”

The team developed an advanced system of sensors and algorithms to allow the robots to function on their own – once given an assignment, they make decisions autonomously on how to best complete it.

Advanced Communication

A major goal is to get them from engineers directly into the hands of first responders. Success requires simplifying the way the robots transmit data into something approximating plain English, according to Kyle Harlow, a computer science PhD student.

“The robots communicate in pure math. We do a lot of work on top of that to interpret the data right now, but a firefighter doesn’t have that kind of time,” Harlow said.

To make that happen Humbert is collaborating with Chris Heckman, an associate professor of computer science, to change both how the robots communicate and how they represent the world. The robots’ eyes – a LiDAR sensor – creates highly detailed 3D maps of an environment, 15 cm at a time. That’s a problem when they try to relay information – the sheer amount of data clogs up the network.

“Humans don’t interpret the environment in 15 cm blocks,” Humbert said. “We’re now working on what’s called semantic mapping, which is a way to combine contextual and spatial information. This is closer to how the human brain represents the world and is much less memory intensive.”

High Tech Mapping

The team is also integrating new sensors to make the robots more effective in challenging environments. The robots excel in clear conditions but struggle with visual obstacles like dust, fog, and snow. Harlow is leading an effort to incorporate millimeter wave radar to change that.

“We have all these sensors that work well in the lab and in clean environments, but we need to be able to go out in places such as Colorado where it snows sometimes,” Harlow said.

Where some researchers are forced to suspend work when a grant ends, members of the subterranean robotics team keep finding new partners to push the technology further.

Autonomous Flight

Eric Frew, a professor of aerospace at CU �鶹ӰԺ, is using the technology for a new National Institute of Standards and Technology competition to develop aerial robots – drones – instead of ground robots, to autonomously map disaster areas indoors and outside.

“Our entry is based directly on the Subterranean Challenge experience and the systems developed there,” Frew said.

Some teams in the competition will be relying on drones navigated by human operators, but Frew said CU �鶹ӰԺ’s project is aiming for an autonomous solution that allows humans to focus on more critical tasks.

Although numerous universities and private businesses are advancing autonomous robotic systems, Humbert said other organizations often focus on individual aspects of the technology. The students and faculty at CU �鶹ӰԺ are working on all avenues of the systems and for uses in environments that present extreme challenges.

“We’ve built world-class platforms that incorporate mapping, localization, planning, coordination – all the high level stuff, the autonomy, that’s all us,” Humbert said. “There are only a handful of teams across the world that can do that. It’s a huge advantage that CU �鶹ӰԺ has.”