{"id":702,"date":"2019-08-16T12:32:41","date_gmt":"2019-08-16T12:32:41","guid":{"rendered":"https:\/\/evhnews.com\/?p=702"},"modified":"2019-12-17T14:29:43","modified_gmt":"2019-12-17T22:29:43","slug":"man-on-the-moon","status":"publish","type":"post","link":"https:\/\/evhnews.com\/es\/2019\/08\/16\/man-on-the-moon\/","title":{"rendered":"Man On The Moon"},"content":{"rendered":"

The creator of the climbing robot is Professor Frank Kirchner, who heads the Robotics Innovation Center at DFKI such as the four-legged walking robot Charlie, which looks Mantis-like. <\/em>Image Credit: Porsche AG &\u00a0Cosima Hanebeck; DFKI<\/em><\/span><\/p>\n

Man On The Moon<\/strong><\/p>\n

In Bremen, the team led by Prof. Frank Kirchner is working on robots for missions in space and underwater. Far from earth, they have to find their way and make decisions independently\u2014 similarly to autonomous vehicles in road traffic.<\/p>\n

The moon has a branch office in Bremen. The slope of the artificial crater is nine meters wide; five-and-a-half meters of elevation must be scaled from the foot of the depression to its top. Those wishing to climb it must overcome inclines of 25 to 40 degrees. People are generally spectators here, though, for this moonscape was designed as a training ground for astronauts of steel: In the space exploration hall at the German Research Center for Artificial Intelligence (DFKI), robots practice independent exploratory missions on the satellite of Earth. The choice of terrain is no accident: Craters and their surroundings are among the most interesting places on moons and planets because their slopes contain sediment layers from different eras, as well as traces of material from the solar system. Their walls also provide information about the origins of moons and planets.<\/p>\n

The creator of the climbing robot is Professor Frank Kirchner, who heads the Robotics Innovation Center at DFKI on the outskirts of Bremen and works on mechanical astronauts with his team. His creatures are often biologically inspired, such as the four-legged walking robot Charlie, which looks like a monkey, or Mantis, a contraption with six extremities that looks like its namesake from the animal kingdom. At present, Coyote III, a gray-and-orange rover with star-shaped wheels and a flattish silhouette is navigating the artificial moonscape.<\/p>\n

Intelligent and autonomous robots are indispensable for space exploration because they require no food and no oxygen. And once the mission is done, they don\u2019t need a return journey to Earth. They do, however, have to be able to hold their own, to some extent, on strange moons and planets. The artificial crater in Bremen provides an opportunity to see how well they do at it. The crater was built by a company that ordinarily builds indoor climbing walls. \u201cThe template was photographs taken by Apollo astronauts of a crater at the Moon\u2019s south pole,\u201d explains Kirchner, one of the world\u2019s foremost experts for autonomous space and underwater robots.<\/p>\n

Autonomous submarine for the moon of Jupiter<\/strong><\/p>\n

Outer space and the underwater world have more in common than one might assume at first glance. One of the most interesting places in the solar system, after all, is Jupiter\u2019s moon Europa, under whose ice sheet a vast ocean of liquid water has been postulated\u2014a place, in other words, in which life could have developed.<\/p>\n

\u201cFor me an autonomous vehicle is a robot I can drive\u201d Professor Frank Kirchner<\/strong><\/p>\n

So the Bremen-based robotics experts have also built an eight-meter-deep water tank in which they can test the Europa Explorer, among other things: The pipe-shaped drill named Teredo is designed to penetrate the 3 to 15-kilometer-thick ice sheet on the moon\u2019s surface and then launch the underwater vehicle Leng to explore the ocean beneath. Because control signals from earth would take 33 to 53 minutes to arrive, the torpedo-shaped submarine would have to be able to operate autonomously.<\/p>\n

It\u2019s no wonder, then, that the research group in the \u201cspace city\u201d of Bremen has been working intensively on topics such as sensor technology, actuator technology, and artificial intelligence. But the results they achieve do not only benefit aerospace applications\u2014 Kirchner also places great store by the transfer to other fields, for instance for robots that have to maneuver independently in dangerous environments. He is also following the development of autonomous driving avidly, from his own very particular perspective. \u201cFor me an autonomous vehicle is a robot I can drive,\u201d says Kirchner.
\n\"Rover<\/p>\n

Sherpa is a rover with an active suspension that can adapt to different terrain and obstacle situations. Image Credit: Porsche AG &\u00a0Cosima Hanebeck; DFKI<\/em><\/span><\/p>\n

And there are, indeed, many commonalities. Both autonomous vehicles and robots on distant orbs must perceive and analyze their surroundings and use that information to make intelligent decisions. Of course on the moon and Mars there is no road traffic with traffic lights, traffic signs and cars and pedestrians suddenly popping out of nowhere. Nevertheless, even Kirchner\u2019s robots have to deal with dynamic conditions such as sandstorms and tornadoes on Mars or starkly changing light conditions on the moon.<\/p>\n

Orientation without maps<\/strong><\/p>\n

In contrast to autonomous vehicles, however, there are no maps of the terrain for their missions. \u201cAt one meter, the resolution of satellite images is still too poor,\u201d explains Kirchner. \u201cAs such, the robots must build their own maps of their environment and locate themselves within it.\u201d To cope with that reality, the researchers developed the SLAM algorithms (Self Localization and Mapping), probability-based methods for orientation in unknown terrain. \u201cIt all started with navigation in sewage canals,\u201d recalls Kirchner. \u201cIt was a very simple environment, which allowed us to test the new approach there very effectively.\u201d From the mid-1990s, the SLAM algorithms were also used in open terrain and in buildings. The first applications for the self-localization of autonomous vehicles emerged about 15 years ago.<\/p>\n

Autonomous vehicles should continue to learn while in use<\/strong><\/p>\n

The basis for the SLAM algorithms is object recognition in dynamic situations, which was also an early focus of the robotics experts. The challenge: The technology must function reliably even when the camera is moving and the ambient conditions change due to weather and changing light conditions\u2014factors that apply as much on Mars as on Earth. \u201cIn robotics, object recognition has gained a great deal in terms of maturity and robustness,\u201d says Kirchner. \u201cThe underlying mathematics is the same as in cars today.\u201d But the transfer is by no means a one-way street. Robot developers have benefited significantly from the smartphone boom of recent years that has made inexpensive video cameras commonplace. And with the continued exponential performance gains with microprocessors\u2014a phenomenon known as Moore\u2019s Law, with considerable impetus from the automotive industry\u2014, their creations are becoming increasingly intelligent.<\/p>\n

\"aila_robot_system_2019_porsche_engineering_gmbh.jpg\"<\/p>\n

The AILA robot system has 32 degrees of freedom, including seven joints per arm. It serves as a platform for research in the field of mobile manipulation. Image Credit: Porsche AG &\u00a0Cosima Hanebeck; DFKI<\/em><\/span><\/p>\n

Based on his own research, he knows how complicated it is to steer a car through road traffic without human intervention. Kirchner himself has ridden in two test vehicles and was \u201cvery impressed.\u201d As a highly engaged observer of the development, he naturally has a few ideas of his own on the subject. \u201cAutonomous vehicles should learn during their use phase,\u201d he suggests. \u201cOne buys a vehicle with basic experience and it continues to develop itself along with the other vehicles on the road.\u201d It would be a collective learning experience\u2014just as with the collaborative robots that are now gaining a foothold in industrial manufacturing processes: They have to get along with a variety of different people and therefore share their individual experiences with each other, for instance via a cloud.<\/p>\n

\u201cToday, with autonomous driving we pay too much attention to the individual algorithms\u2014but we\u2019ve known them for a long time already, in some cases since the 1950s,\u201d says Kirchner. \u201cWhat\u2019s more important is the organization of knowledge. They key is to network the individual components of knowledge with each other\u2014for instance through collective learning. The vehicle must be a system that learns throughout its life.\u201d And to do so, it should also dream from time to time: Kirchner\u2019s team is working on the EU project Dreams4Cars, whose mission is to improve the safety of autonomous vehicles. Like mind\u2019s-eye pictures or dreams, the control software continually replays real traffic situations in a simulation environment, testing alternative reactions and thereby preparing itself for exceptional circumstances. It will be interesting to see what ideas from the Bremen-based robotics experts eventually make their way from the moon to Earth.<\/p>\n

Text: Christian Buck
\nPhotos: Cosima Hanebeck; DFKI<\/p>\n

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The creator of the climbing robot is Professor Frank Kirchner, who heads the Robotics 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