The distributed co-evolution of an on-board simulator and controller for swarm robot behaviours

Abstract

The distributed co-evolution of an on-board simulator and controller for swarm robot behaviours. Evolutionary Intelligence, 7 (2). pp. 95-106. ISSN 1864-5909 Available from: http://eprints.uwe.ac.uk/23450We recommend you cite the published version. The publisher's URL is: http://dx.doi.org/10.1007/s12065-014-0112-8 Refereed: YesThe final publication is available at Springer via http://dx.doi.org/doi:10.1007/s12065?014?0112?8 Disclaimer UWE has obtained warranties from all depositors as to their title in the material deposited and as to their right to deposit such material. UWE makes no representation or warranties of commercial utility, title, or fitness for a particular purpose or any other warranty, express or implied in respect of any material deposited.UWE makes no representation that the use of the materials will not infringe any patent, copyright, trademark or other property or proprietary rights. UWE accepts no liability for any infringement of intellectual property rights in any material deposited but will remove such material from public view pending investigation in the event of an allegation of any such infringement. PLEASE SCROLL DOWN FOR TEXT.Noname manuscript No. Abstract We investigate the reality gap, specifically the environmental correspondence of an on-board simulator. We describe a novel distributed co-evolutionary approach to improve the transference of controllers that co-evolve with an on-board simulator. A novelty of our approach is the the potential to improve transference between simulation and reality without an explicit measurement between the two domains. We hypothesise that a variation of on-board simulator environment models across many robots can be competitively exploited by comparison of the real controller fitness of many robots. We hypothesise that the real controller fitness values across many robots can be taken as indicative of the varied fitness in environmental correspondence of on-board simulators, and used to inform the distributed evolution an on-board simulator environment model without explicit measurement of the real environment. Our results demonstrate that our approach creates an adaptive relationship between the onboard simulator environment model, the real world behaviour of the robots, and the state of the real environment. The results indicate that our approach is sensitive to whether the real behavioural performance of the robot is informative on the state real environment.

Evolutionary online behaviour learning and adaptation in real robots

“…To the best of our knowledge, this experiment is the first instance of online evolution of collectively coordinated behaviours with real robots. Previous studies involving multiple robots have been limited to individual tasks such as phototaxis [ 25 ], dynamic phototaxis [ 3 ], foraging [ 26 ], and a combination of foraging and phototaxis (robots can use a moving light source as an environmental aid) in which controllers are evolved in an on-board simulator [ 27 ].…”

Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment

“…Furthermore, in some of these recent studies, swarm robots did not only solve complex tasks, but also unveiled some interesting evolutionary patterns and adaptations. For instance, during simulation, co-evolution has been observed between different robot populations, which eventually would lead to improved adaptation (Nolfi & Floreano, 1998; O’Dowd, Studley & Winfield, 2014; Ferrante et al, 2015). …”

A Two Teraflop Swarm

“…When applied to swarms (Watson et al, 2002 ) the evolutionary algorithm is distributed over the robots (Takaya and Arita, 2003 ; Bredeche et al, 2012 ; Doncieux et al, 2015 ). Other approaches use reality sampling to alter the simulated environment to better match true fitnesses (Zagal et al, 2004 ; O’Dowd et al, 2014 ). This requires either off-board processing with communication links to the robot or sufficient processing power on the robot to run simulations.…”

“…Messages received have no content, but are an indication that the sender and the receiver can communicate, actual data transfer can take place point-to-point. In this, we take inspiration from O’Dowd et al ( 2014 ), who use IR communication between e-pucks to establish if contact is possible, data transfer then taking place over WiFi.…”