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Implementing Secondary Swarming - UWE Intelligent Autonomous ...

Implementing Secondary Swarming - UWE Intelligent Autonomous ...

Implementing Secondary Swarming - UWE Intelligent Autonomous

Gradient Ascent with a group of Minimalist Real Robots: ImplementingSecondary SwarmingChris Melhuish, Jason WelsbyIntelligent Autonomous Systems (Engineering) LaboratoryFaculty of Engineering, University of the West of EnglandColdharbour Lane, Frenchay, Bristol BS16 1QY , EnglandPhil Greenway, BAE Systems, Filton, Bristol, EnglandChris.melhuish@uwe.ac.uk, jason3.welsby@uwe.ac.uk, phil.greenway@baesystems.comAbstract--This paper addresses and highlights some of theproblems facing designers and those who engineer smallscale robots in the future. It specifically looks at the problemof small-scale robots ascending a gradient field. Inparticular the performance of an individual, minimalistrobot can be improved when a group of similarly limitedrobots is employed; being a member of a collective confersbenefit to the individual. The paper describes theimplementation of simulation work with a group of real‘blimp’ robots, with a severely restricted payload,demonstrating that spatial integrity of a group of agentsaround a target can be improved when employing themechanism of secondary swarmingIndex Terms— collective behaviour, swarming,minimalist, autonomous.I. INTRODUCTIONThe principle aim of this paper is to describe theimplementation of a set of collective minimalistalgorithms on a group of real autonomous robots,severely limited in their computation, communicationand sensing capabilities in order to realise the ideasdemonstrated in earlier simulation work. Theminimalist challenge was faced ‘head on’ with thedecision to employ a helium balloon robots with apayload of 93g.There may be advantages in the use ofcollective robotics to perform a task reliably withminimal computation, sensing and communication. Acollective group has built in redundancy, in that it canwithstand a certain amount of agent loss and stillachieve its goal, whereas a solitary complex robot maybe disabled by the loss of a single sub-system, makingthe task impossible. Recently, engineers have drawn onsuch lessons from Nature and developed groups ofsimple autonomous mobile robots, which use simplerules to act co-operatively in the pursuit of a sharedgoal. The roots of minimalism spring from the study ofwhat are sometimes called ‘lower animals’, where‘lower’ relates to the degree of behaviouralsophistication. Through what we perceive to be simplebehaviours, collections of such animals can performincredible tasks, transcending the capability of theindividual. Recently great interest has arisen in the areaof collective systems, and many researchers are usingtechniques inspired by nature to implement multiplerobotic systems [Kube & Zhang (1992), Mataric(1994), Beckers, Holland & Deneubourg (1994), Kelly& Keating (1996), Melhuish, (1999)]. For example,‘studies of social insects show us that groups ofindividuals, limited in their ability, can collectivelyachieve remarkable feats … [which] appear to beachieved without recourse to many of the aspects oftenconsidered necessary for intelligent behaviour’[Melhuish, 1999].Strategies were developed which involved nointeraction between agents (referred to as pseudoswarming)as well as those which required simpleinteraction between agents in the form of thetransmission and detection of a simple secondary fieldgenerated by the agents themselves (referred to assecondary swarming). Holland and Melhuish (1996)showed that performance improvements for the task ofhoming on a beacon could be achieved but at the costof incorporating additional capabilities to the simulatedrobots.It was argued that an agent could ‘home-in’ onthe target if it could detect it. On detection of the targetit would also generate a secondary ‘localised’ field.

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