Modular scalable robot control

This paper proposes a data fusion and control distribution technique in fully decentralized systems. Nonfully connected control topologies based on internodal transformations are formulated. This is achieved by distributing the state models, observation spaces and control vectors in an information filter based, decentralized control configuration. There is no central processing site and distribution reduces the computational burden at each node. Communication, just as connectedness, is based on internodal transformations and is dynamically defined. Consequently, only relevant information is exchanged between nodes and there is no need for inter-nodal (Channel) filters. The result is a flexible, robust, parallel, scalable and globally optimal control network. The design is implemented using transputer based parallel hardware. Application envisaged is distributed intelligent control for a modular mobile robot. This is composed of independent driven and steered modules, each with its own sensors, communication and control