TY - JOUR
T1 - Cooperative Object Transport with a Swarm of E-puck Robots
T2 - Robustness and Scalability of Evolved Collective Strategies
AU - Alkilabi, Muhanad Hayder Mohammed
AU - Narayan, Aparajit
AU - Tuci, Elio
N1 - Funding Information:
Muhanad H. Mohammed Alkilabi thanks Iraqi Ministry of Higher Education and Scientific Research for funding his PhD. The authors would like to thank G. Francesca and M. Birattari for their support with the statistical analysis of the physical robots performances.
Publisher Copyright:
© 2017, Springer Science+Business Media New York.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Cooperative object transport in distributed multi-robot systems requires the coordination and synchronisation of pushing/pulling forces by a group of autonomous robots in order to transport items that can not be transported by a single agent. The results of this study show that fairly robust and scalable collective transport strategies can be generated by robots equipped with a relatively simple sensory apparatus (i.e., no force sensors, and no devices for direct communication). In the experiments described in this paper, homogeneous groups of physical e-puck robots are required to coordinate and synchronise their actions in order to transport a heavy rectangular cuboid object as far as possible from its starting position to an arbitrary direction. The robots are controlled by dynamic neural networks synthesised using evolutionary computation techniques. The best evolved controller demonstrates an effective group transport strategy that is robust to variability in the physical characteristics of the object (i.e., object mass, and size of the longest object's side) and scalable to different group sizes. To run these experiments, we designed, built, and mounted on the robots a new sensor that returns the agents' displacement on a 2D plane. The study shows that the feedback generated by the robots' sensors relative to the object's movement is sufficient to allow the robots to coordinate their efforts and to sustain the transports for an extended period of time. By extensively analysing successful behavioural strategies we illustrate the nature of the operational mechanisms underpinning the coordination and synchronisation of actions during group transport.
AB - Cooperative object transport in distributed multi-robot systems requires the coordination and synchronisation of pushing/pulling forces by a group of autonomous robots in order to transport items that can not be transported by a single agent. The results of this study show that fairly robust and scalable collective transport strategies can be generated by robots equipped with a relatively simple sensory apparatus (i.e., no force sensors, and no devices for direct communication). In the experiments described in this paper, homogeneous groups of physical e-puck robots are required to coordinate and synchronise their actions in order to transport a heavy rectangular cuboid object as far as possible from its starting position to an arbitrary direction. The robots are controlled by dynamic neural networks synthesised using evolutionary computation techniques. The best evolved controller demonstrates an effective group transport strategy that is robust to variability in the physical characteristics of the object (i.e., object mass, and size of the longest object's side) and scalable to different group sizes. To run these experiments, we designed, built, and mounted on the robots a new sensor that returns the agents' displacement on a 2D plane. The study shows that the feedback generated by the robots' sensors relative to the object's movement is sufficient to allow the robots to coordinate their efforts and to sustain the transports for an extended period of time. By extensively analysing successful behavioural strategies we illustrate the nature of the operational mechanisms underpinning the coordination and synchronisation of actions during group transport.
KW - Collective transport
KW - Swarm robotics
KW - Evolutionary computation
KW - Artificial neural networks
UR - http://www.scopus.com/inward/record.url?scp=85016546806&partnerID=8YFLogxK
U2 - 10.1007/s11721-017-0135-8
DO - 10.1007/s11721-017-0135-8
M3 - Article
SN - 1935-3812
VL - 11
SP - 185
EP - 209
JO - Swarm Intelligence
JF - Swarm Intelligence
IS - 3-4
ER -