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

Proposes a method of effective knowledge sharing among multiple robots by using storage devices which can be attached to the environment. If the robots store knowledge about the environment in these devices, the robots can use the stored knowledge and reduce the cost of achieving their tasks. Since the memory size of such storage device is limited, the robots cannot store all of the required knowledge. Therefore, the robots store knowledge according to its usefulness, which is defined by the reducible cost per unit time. A memory unit that is not useful to the robot in which it is stored can be copied to a storage device and deleted from the robot. It is then available, on the device, for any robot that requires it. Then the robots can store useful knowledge over the whole environment, and the memory units are flexibly re-located according to the given tasks. A simulation result of multiple robot navigation for repetitive transportation tasks shows the effectiveness of our method