{"id":397191,"date":"2022-01-21T15:16:20","date_gmt":"2022-01-21T12:16:20","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/how-robots-learn-to-hike\/"},"modified":"2022-01-21T15:16:20","modified_gmt":"2022-01-21T12:16:20","slug":"how-robots-learn-to-hike","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/how-robots-learn-to-hike\/","title":{"rendered":"#How robots learn to hike"},"content":{"rendered":"

“#How robots learn to hike<\/strong>”<\/p>\n

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\n The legged robot ANYmal on the rocky path to the summit of Mount Etzel, which stands 1,098 metres above sea level. Credit: Takahiro Miki
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ETH Zurich researchers led by Marco Hutter developed a new control app<\/a>roach that enables a legged robot, called ANYmal, to move quickly and robustly over difficult terrain. Thanks to machine learning, the robot can combine its visual perception of the environment with its sense of touch for the first time.<\/p>\n

Steep sections on slippery ground, high steps, scree and forest trails full of roots: the path up the 1,098-meter-high Mount Etzel at the southern end of Lake Zurich is peppered with numerous obstacles. But ANYmal, the quadrupedal robot from the Robotic Systems Lab at ETH Zurich, overcomes the 120 vertical meters effortlessly in a 31-minute hike. That’s 4 minutes faster than the estimated duration for human hikers\u2014and with no falls or missteps.<\/p>\n

This is made possible by a new control technology<\/a>, which researchers at ETH Zurich led by robotics professor Marco Hutter recently presented in the journal Science<\/a> Robotics<\/i>. “The robot has learned to combine visual perception of its environment with proprioception\u2014its sense of touch\u2014based on direct leg contact. This allows it to tackle rough terrain faster, more efficiently and, above all, more robustly,” Hutter says. In the future, ANYmal can be used anywhere that is too dangerous for humans or too impassable for other robots.<\/p>\n

Perceiving the environment accurately<\/b><\/p>\n

To navigate difficult terrain, humans and animals quite automatically combine the visual perception of their environment with the proprioception of their legs and hands. This allows them to easily handle slippery or soft ground and move around with confidence, even when visibility is low. Until now, legged robots have been able to do this only to a limited extent.<\/p>\n

“The reason is that the information about the immedia<\/a>te environment recorded by laser sensors and cameras is often incomplete and ambiguous,” explains Takahiro Miki, a doctoral student in Hutter’s group and lead author of the study. For example, tall grass, shallow puddles or snow appear as insurmountable obstacles or are partially invisible, even though the robot could actually traverse them. In addition, the robot’s view can be obscured in the field by difficult lighting conditions, dust or fog.<\/p>\n

“That’s why robots like ANYmal have to be able to decide for themselves when to trust the visual perception of their environment and move forward briskly, and when it is better to proceed cautiously and with small steps,” Miki says. “And that’s the big challenge.”<\/p>\n

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