Cooperative Localization for Mobile Agents: A Recursive Decentralized Algorithm Based on Kalman-Filter Decoupling

Technological advances in ad hoc networking and the miniaturization of electromechanical systems are making possible the use of large numbers of mobile agents (for example, mobile robots, human agents, and unmanned vehicles) to perform surveillance, search and rescue, transport, and delivery tasks in aerial, underwater, space, and land environments. However, the successful execution of such tasks often hinges upon accurate position information, which is needed in lower-level locomotion and path-planning algorithms. Common techniques for the localization of mobile robots are the classical preinstalled beacon-based localization algorithms, fixed feature-based simultaneous localization and mapping (SLAM) algorithms, and Global Positioning System (GPS) navigation. However, these localization techniques work based on assumptions such as the existence of distinct and static features that can be revisited often or line of sight to GPS satellites, which may not be feasible for operations such as search and rescue, environment monitoring, and oceanic exploration. In the case of GPS navigation, there is also a current concern about signal jamming for outdoor navigation, especially for unmanned aerial vehicle coordination and control. Instead, cooperative localization is emerging as an alternative localization technique that can be employed in such scenarios.