ACELLULAR CONTROL ARCHITECTURE FOR AUTONOMOUS ROBOTS

Proceedings 1994 International Workshop on Intelligent

Robotic Systems (IRS’94), Grenoble, July 1994, pp. 70-79.

A CELLULAR CONTROL ARCHITECTURE FOR AUTONOMOUS ROBOTS

Elpida S. Tzafestas

LAFORIA-IBP, Université Pierre et Marie Curie,

4, Place Jussieu, 75252 Paris Cedex 05, FRANCE

e-mail : brensham@laforia.ibp.fr

ABSTRACT

This paper presents a cellular control architecture for autonomous robots. This architecture, which is an

instanciation of the behaviour-based paradigm, i) defines the cell as the elementary unit of storage and processing

and categorises cells into functionally different types, ii) imposes a three-level nested structure (cells, aggregates

of cells, tasks), iii) decouples structured activity from reflex as well as from arbitration between tasks, through

use of special actuator command systems where all reflexes are situated and definition of arbitration in terms of

actuators by employing one dedicated arousal system for each task. Adaptation is defined as reinforcement or

replacement at the cell level, but its effects spread through the network according to the cell's position. It is

shown that the architecture does not suffer from certain limitations of previous approaches and it is argued that

its modularisation and compositionality constitute good foundation principles for extensibility. Its potential for

cognitive research is sketched and its validity and adequacy for robot population design shown on the basis of

more formal criteria as well as on a set of examples.

1. Introduction

The definition of this architecture is part of a larger project which has as its goal to identify design

principles for populations of autonomous robots. Given a high-level task, such as exploration of a region or

supervision of an industrial site, a designer faces the problem of how to distribute this task across a number of

robots, namely, what are the basic activities a robot should engage in and how to combine them efficiently. It is

then essential to adopt a robot control architecture that allows for integration and implementation of various such

activities with minimum effort. On the other hand, in order to identify the relation between global high-level

tasks and local structure of the robots, one needs to be able to mutate this structure easily so as to systematise the

comparative study. On a methodological ground, this implies we do not believe in general-purpose local

structures, fit for all kinds of tasks, but rather in structures amenable to parameterisation, which are suitable for

classes of tasks. A comparative study will then focus on the identification of those local parameters that affect

performance and that need to drive the design process.

An initial choice was to remain in the reactive, behaviour-based paradigm which was shown (Brooks

1991) to have many desirable properties: no central world representation bottlenecks, minimisation of time lags

between perception and actuator level command output, fault-tolerance and low implementation cost. In one

word, the power of the behaviour-based paradigm lies in its simplicity. It is left to the interaction with the world

to give rise to complex phenomena, and it is this potential emergent complexity that researchers in this area try to

tame and exploit.

To allow systematisation of study, the robot control architecture then needs to fulfill the following

requirements:

1) Extensibility. One needs to be able to easily add new structural possibilities, either components or

connections, and study their individual impact as well as their interactions.

2) Specification construction possibility. One needs to be able to define a one-to-one relation between

an instance of the architecture and a specification. During design it is the specification that will be manipulated,

so that it must be ensured that this specification induces no ambiguity on the actual structure of the robot's

control system. This specification serves the double role of being the output product of the design process as wellas the experimentation building block. Actually, experimentation is the process of associating robot

specifications to high-level task performances, while design is the inverse problem of finding the robot

specification that will be best suitable to a task at hand.

3) Parameter instanciation possibility. Finally, one needs to explicitly define the parameters that

constitute this specification and whose impact one intends to study. Admittedly, not all of these parameters will

be of interest in different contexts. The goal of the comparative study is then to discover those that actually play a

role and translate this role into design knowledge.