Towards robust multi-robot formations

Robots in formations move while maintaining a predefined geometric shape. Previous work has examined formation-maintenance algorithms that would ensure the stability of the formation. However, for each geometric formation, an exponential number of stable controllers exists. Thus a key question is how to select (construct) a formation controller that optimizes desired properties, such as sensor usage for robustness. This paper presents a monitoring multi-graph framework for formation controller selection, based on sensor-morphology considerations. We instantiate the framework, and present two contributions. First, we show that graph-theoretic techniques can then be used to compute sensing policies that maintain a given formation. In particular, sensor-based control laws for separation-bearing (distance-angle) formation control can be automatically constructed. Second, we present a protocol allowing controllers to be switched on-line, to allow robots to adjust to sensory failures. We report on results from comprehensive experiments with physical robots. The results show that the use of the dynamic protocol allows formations of physical robots to move significantly faster and with greater precision, while reducing the number of formation failures.