Distributed networked robot systems consist of multiple robots that are connected by communication. In these systems the robots interact locally with the environment. The objective is for the system as a whole to have guaranteed global behavior. Distributed robotics is an important area of robotics as it addresses how collections of robots can collaborate to achieve a larger task than each individual robot is capable of doing. We are developing algorithms and systems that (1) enable collaboration; (2) couple tightly communication, control, and perception; (3) are scalable and generally independent on the number of agents in the system; (4) have provable guarantees. Our contributions include adaptive control for coverage when the sensory function is not known, adaptive control for communication coverage with mobile base stations, persistent surveillance, information-theoretic planning and control, Linear Temporal Logic (LTL) approaches to planning and control that model priorities and hierarchical tasks, optimization for mobility on demand and other traffic applications, and optimization for multi robot assembly.