Fuzzy Logic Mobility Controller for
Navigational Strategies and Mobility Controls of Group of Mobile Robotic
Vehicles
This research addresses issues regarding mobility behaviors of a group
of robots for optimum steering and gap control. The central emphasis of
this 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. Though, this approach is used for limited predefined
basic tasks that cover most of the relevant MRVs mobility behaviors. We
have divided basic tasks in 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 FMCell simulation environment and is able to control
a group of up to 16 MRVs. In this research, we present some of the simulation
results of our research investigation using FMCell.
