A Unified Methodology for Multi-Robot Passive & Active Sensing

A major barrier preventing the wide employment of mobile networks of robots in tasks such as exploration, mapping, surveillance, and environmental monitoring is the lack of efficient and scalable multi-robot passive and active sensing (estimation) methodologies. The main reason for this is the absence of theoretical and practical tools that can provide with computationally tractable methodologies which can deal efficiently with the highly nonlinear and uncertain nature of multi-robot dynamics when employed in the aforementioned tasks. In this paper, a new approach is proposed and analyzed for developing efficient and scalable methodologies for a general class of multi-robot passive and active sensing applications. Given the computational, communication, etc requirements of the particular multi-robot sensing application, the proposed methodology provides with an estimator design that meets the aforementioned requirements and, moreover, (a) guarantees stable and convergent performance of the aforementioned estimator and (b) provides with an estimation accuracy that is inversely proportional to the complexity of the aforementioned estimator (which, in turn, is proportional to either the computational capabilities of the robot's equipment or its memory storage capabilities). The proposed approach can handle various types of constraints such as communication and computational constraints as well as obstacle avoidance and maximum speed constraints and can treat both problems of passive and active sensing in a unified manner. The application of the proposed methodology to various multi-robot sensing tasks such as robot pose estimation using only inter-robot distance measurements, target tracking and simultaneous localization, mapping and exploration is discussed.