Tactical mobility and navigational strategies of a group of mobile robots using fuzzy logic

Addresses issues regarding mobility behaviors of a group of robots for optimum steering and gap control. The central emphasis of the paper is focused on achieving a dynamic adaptation of different fuzzy behaviors for successful tactical configurations and mobility controls of mobile robotic vehicles (MRV). The different mobility behaviors in a fuzzy logic mobility controller (FLMC) can be categorized as goal seeking behavior, leader-follower behavior, obstacle avoidance behavior, and target tracking behavior. This approach is used for limited predefined basic tasks that cover most of the relevant MRVs mobility behaviors. We have divided basic tasks into two categories, group tasks and individual tasks. Group tasks such as marching, merging, splitting, and exploratory movements are some of the challenging group tasks. On the other hand, some of the individual tasks are environment exploration, isolated navigation, and target searching. The proposed FLMC reduces instability problems associated with group mobility control of MRVs and improves overall reliability and stability in handling different mobility situations. The proposed FLMC has been developed in the FMCell simulation environment and is able to control a group of up to 16 MRVs. We present some of the simulation results of our research investigation using FMCell.