Check out a video of the little machine in action—it’s pretty darn cute. “Animals are capable of precise and agile locomotion using vision. Replicating this ability has been a long-standing goal in robotics,” the Carnegie Mellon research team explains in their YouTube video‘s description, before explaining that the robot’s systems were first trained through trial and error in simulation environments of areas like staircases and stepping stones. Once the team completed that phase, their four-legged walker utilized its onboard video camera to process what was in front of it while referring back to its previous reinforcement training to adapt as needed. According to Technology Review, the lack of pre-trial mapping is a major leap forward (so to speak) for mobile robots, as a better, more consistent real-time analysis of surroundings could one day greatly widen their accessibility and deployment. Although the team’s quadruped still has some trouble with slippery surfaces and visually noisy environments like tall grass, the progress remains incredibly impressive ahead of the project’s big debut at next month’s Conference on Robot Learning.
