| In a large group of robots, which in the scope of this thesis is called a collective, the capabilities of the collective are often greater than the sum of the capabilities of the individual robots that make up that collective. This additional capability can be the result of the overall collective shape, and/or the robots' changing their behavior based on their location within the collective, defined as differentiation. These properties of the collective, namely the shape and the overall differentiation of robots in the shape (the desired spatial-temporal role pattern), can add capabilities to a collective, and therefore they are important to control. In the event that the shape of the collective and/or the spatial-temporal role pattern is damaged, then the collective can lose some or all of the capabilities gained by those properties. If the collective could re-gain the lost properties through self-healing, then it is possible to recover the lost capabilities as well. This self-healing could be possible if the robots are capable of moving to a new location within the collective, as well as changing their differentiated behavior.;In this thesis, a distributed control method called DASH ( distributed self-assembly and self-healing) is presented, which empowers a collective of robots to robustly and consistently form and maintain a pre-defined shape and spatial-temporal role pattern. Furthermore, a control method called S-DASH (scalable distributed self-assembly and self- healing) allows the shape and spatial-temporal role pattern to be formed at a scale proportional to the number of robots currently in the collective. If this collective shape or spatial-temporal role pattern is damaged through the un-controlled movement, removal, or addition of some members of the collective, the existing members will recover the desired shape and spatial-temporal role pattern proportional to the new number of robots in the collective. The control methods are analyzed in terms of the class of acceptable shapes, how well it scales to the number of robots in the collective, and convergence to the desired shape and spatial-temporal role pattern. The control methods are then demonstrated in a simulated collective of simple robots. |
