Atlas Robot Can Navigate Its Way Through Narrow Space And Uneven Terrain
Sundar Pichai - Jul 17, 2019
Boston Dynamics recently published a video regarding its humanoid robot Atlas which can walk on uneven surfaces on its own
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Boston Dynamics, an American engineering and robotics design company, recently published a video regarding its humanoid robot Atlas. Following that, it now can walk on an uneven surface, a leap from the first time it appeared in public.
Back in 2013, Atlas was able to walk over flat terrain, but it needed supports from engineers who operated the machine through a user interface. That was one of the reasons why the robot fell in The Defense Advanced Research Projects Agency’s (DARPA) Robotics Challenge in 2015. Since then, the robot has considerably improved on both features and movement capabilities.
With the new software designed by the Institute for Human and Machine Cognition (IHMC), Atlas does not need a human operator anymore.
At first, IHMC’s algorithm skims through the environment around the robot using its sensors; then, it segments the objects into different sections. Data collected helps to create a model of the environment in the form of polygon series. Based on that, Atlas itself plans each step to walk through obstacles.
With this new method, Atlas is believed to be able to cover both flat and uneven surface. It even can get through narrow spaces. When it is complete, the robot will open new opportunities to rescue victims during disaster events, which has always been a challenging task for traditional rescue services.
According to IHMC’s announcement, the new software works flawlessly on flat grounds. When it comes to the narrow and rough environment, it still shows some flaws as the robot might fall sometimes. Official statistics show that on rough terrain, the robot has a success rate of 90%, while on narrow ground, the figure is 50%.
Another robot also making impressive progress is Valkyrie from NASA’s Johnson Space Center. Unlike Atlas, Valkyrie maps out only a few steps before its actual move. The method makes it more adaptive to changes in paths, and reach the goal much more quickly.
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