MIT’s Cheetah 3 robot can now leap and gallop across rough terrain, climb a staircase littered with debris, and quickly recover its balance when suddenly yanked or shoved, all while essentially blind.
The 90-pound mechanical beast — about the size of a full-grown Labrador — is intentionally designed to do all this without relying on cameras or any external environmental sensors. Instead, it nimbly “feels” its way through its surroundings in a way that engineers describe as “blind locomotion,” much like making one’s way across a pitch-black room.
Cheetah 3 is designed to do versatile tasks such as power plant inspection, which involves various terrain conditions including stairs, curbs, and obstacles on the ground.
The Cheetah 3 can blindly make its way up staircases and through unstructured terrain, and can quickly recover its balance in the face of unexpected forces, thanks to two new algorithms developed by the team: a contact detection algorithm, and a model-predictive control algorithm.
The contact detection algorithm helps the robot determine the best time for a given leg to switch from swinging in the air to stepping on the ground. For example, if the robot steps on a light twig versus a hard, heavy rock, how it reacts — and whether it continues to carry through with a step, or pulls back and swings its leg instead — can make or break its balance.
The contact detection algorithm helps the robot determine the best time to transition a leg between swing and step, by constantly calculating for each leg three probabilities: the probability of a leg making contact with the ground, the probability of the force generated once the leg hits the ground, and the probability that the leg will be in midswing.
The algorithm calculates these probabilities based on data from gyroscopes, accelerometers, and joint positions of the legs, which record the leg’s angle and height with respect to the ground.
The researchers tested the algorithm in experiments with the Cheetah 3 trotting on a laboratory treadmill and climbing on a staircase. Both surfaces were littered with random objects such as wooden blocks and rolls of tape.
The model-predictive control algorithm calculates the multiplicative positions of the robot’s body and legs a half-second into the future, if a certain force is applied by any given leg as it makes contact with the ground.
The team had already added cameras to the robot to give it visual feedback of its surroundings. This will help in mapping the general environment, and will give the robot a visual heads-up on larger obstacles such as doors and walls. But for now, the team is working to further improve the robot’s blind locomotion.
News Source: http://news.mit.edu/2018/blind-cheetah-robot-climb-stairs-obstacles-disaster-zones-0705
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