Cassie, a bipedal robot that’s all legs, has successfully ran five kilometers without having a tether and on a single charge. The machine serves as the basis for Agility Robotics’ delivery robot Digit, as TechCrunch notes, though you may also remember it for “blindly” navigating a set of stairs. Oregon State University engineers were able to train Cassie in a simulator to give it the capability to go up and down a flight of stairs without the use of cameras or LIDAR. Now, engineers from the same team were able to train Cassie to run using a deep reinforcement learning algorithm.
According to the team, Cassie teaching itself using the technique gave it the capability to stay upright without a tether by shifting its balance while running. The robot had to learn to make infinite subtle adjustments to be able to accomplish the feat. Yesh Godse, an undergrad from the OSU Dynamic Robotics Laboratory, explained: “Deep reinforcement learning is a powerful method in AI that opens up skills like running, skipping and walking up and down stairs.”
The team first tested Cassie’s capability by having it run on turn for five kilometers, which it finished with a time of 43 minutes and 49 seconds. Cassie finished its run across the OSU campus in 53 minutes, 3 seconds — it took a bit longer, because it included six-and-a-half minutes of dealing with technical issues. The robot fell once due to a computer overheating and then again after it executed a turn too quickly. Jeremy Dao, another team member from the lab, though, said they were able to “reach the limits of the hardware and show what it can do.” The work the team does will help expand the understanding of legged locomotion and could help make bipedal robots become more common in the future.
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