For a group of wirelessly networked robots, called "a robot swarm," to accomplish a unified task as a group, it is necessary to generate a set of common coordinates among all member robots and to notify each member robot of its heading direction in the generated common coordinates. However, when the member robots are not equipped with sensors to identify their locations or bearings, they can use only a ranging capability based in the wireless communication protocol being used to network them as a tool to generate a set of common coordinates among them. This paper presents the detailed principles of a method for generating a set of common coordinates/heading direction for a robot swarm with only ranging capability which we have proposed so far. After showing the theoretical Cramer-Rao lower-bound on the location estimation error variance, we demonstrate several computer simulation results for the proposed method with Received Signal Strength Indication (RSSI)-based ranging.

This paper presents a distributed approach for adaptive flocking of swarms of mobile robots that enables to navigate autonomously in complex environments populated with obstacles. Based on the observation of the swimming behavior of a school of fish, we propose an integrated algorithm that allows a swarm of robots to navigate in a coordinated manner, split into multiple swarms, or merge with other swarms according to the environment conditions. We prove the convergence of the proposed algorithm using Lyapunov stability theory. We also verify the effectiveness of the algorithm through extensive simulations, where a swarm of robots repeats the process of splitting and merging while passing around multiple stationary and moving obstacles. The simulation results show that the proposed algorithm is scalable, and robust to variations in the sensing capability of individual robots.