Xbot

Can a simple machine be made to move and carry out a designated task in an unknown area cell? The uncertainty factor and the number of options available to the robot require huge computation resources. Intuitively, I thought that there had to be a simple way. In my study I examined existing solutions and learned of a resource-intensive development of learning systems that rely on a kind of behavioral evolutions, simulating how a robot can overcome obstacles by way of reinforcement learning. As a designer, I sought an unusual solution for the scenario defined and chose to study animal behaviors as an inspiration. I focused on so-called “brainless” animals in order to neutralize the learning factor. I looked for genetically programmed behaviors that enable these animals to carry out tasks. Later in the study, I focused on the slime mold. This fungus scans the space around it to locate food using multiple hyphae or “arms”. These are designed to locate the most efficient route to the food. Once it is found, all arms are directed to it. Hence the inspiration for my solution: a swarm of simple robots that behave identically. The question now was, how could this swarm be used to perform a task in an unknown space more quickly and efficiently than a single robot. The use of multiple, simple robots has created collective behavior allowing the swarm to do the job.