Hexapod Robot Learns to Walk Straight After Suffering Leg Damage

Researchers Antoine Cully, Jeff Clune and Jean-Baptiste Mouret unveiled last year a robot that could teach itself to walk after having one of its legs cut off. The following hexapod robot is an improved version of that.

Being able to adapt is one of the mandatory conditions of evolution. However, when talking about robots, the word evolution might make no sense to some. This concept, which may seem abstract in this context, is indeed possible, as demonstrated by the three researchers. The hexapod robot that they built can adapt to injury, but I’m rather sure that its learning mechanism could be used for other tasks, as well.

As usual, people started arguing that once robots learn to recover from situations that until now seemed with no exit, the human race will meet its end. Others are simply impressed by the fact that the robot is capable of learning, and that it can adapt to new situations such as having a broken leg.

As part of the learning process, the robot acknowledges the injury and start calculating possible solutions to the problem. When one of the best solutions is found (which only takes a few seconds), it is implemented, and the hexapod robot starts walking as if the broken leg did not even exist.

The three researchers who developed this hexapod robot even wrote a paper titled “Robots that can adapt like natural animals” in which they explain how the trial and error algorithm “allows robots to adapt to damage in less than two minutes, thanks to intuitions that they develop before their mission and experiments that they conduct to validate or invalidate them after damage. The result is a creative process that adapts to a variety of injuries, including damaged, broken, and missing legs. This new technique will enable more robust, effective, autonomous robots and suggests principles that animals may use to adapt to injury.”

The hexapod robot faced two challenges that affected one of its legs, but it turned out victorious in both situations. First of all, one of its legs lost power, while in the second scenario, the leg had been broken entirely. This did not stop the robot from assessing its current situation and adapting to the new rules of the game as needed, pretty much as wild animals do.

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