Adaptive relocation of environment-attached storage devices for effective knowledge-sharing among multiple robots

We propose a method of effective knowledge-sharing among multiple robots by using storage devices which can be attached into environment. If robots store knowledge about environment to the devices, robots can use the stored knowledge and reduce cost for achieving tasks. Since memory size of such storage device is limited, robots cannot store all of required knowledge. Therefore the robots store knowledge according to its usefulness defined by reducible cost per time. A memory unit storing useless knowledge is removed from the device and added to the device that requires more useful knowledge. Then the robots can store useful knowledge over the whole environment, and the memory units are flexibly relocated according to the given tasks. A simulation result of multiple robot navigation for repetitive transportation tasks shows the effectiveness of our method.