Fully Decentralized Estimation and Control for a Modular Wheeled Mobile Robot

Abstract

In this paper, the problem of fully decentralized data fusion and control for a modular wheeled mobile robot (WMR) is addressed. This is a vehicle system with nonlinear kinematics, distributed multiple sensors, and nonlinear sensor models. The problem is solved by applying fully decentralized estimation and control algorithms based on the extended information filter. This is achieved by deriving a modular, decentralized kinematic model by using plane motion kinematics to obtain the forward and inverse kinematics for a generalized simple wheeled vehicle. This model is then used in the decentralized estimation and control algorithms. WMR estimation and control is this obtained locally using reduced order models with reduced communication requirements, in a scalable network of control nodes. If communication of information between nodes is carried out after every measurement (full rate communication), the estimates and control signals obtained at each node are equivalent to those obtained by a corresponding centralized system. Transputer architecture is used as the basis for hardware and software design as it supports the extensive communication and concurrency requirements that characterize modular and decentralized systems. The advantages of a modular WMR vehicle include scalability, application flexibility low prototyping costs, and high reliability.