caa a22 4500 463206940 CHVBK 20180405153129.0 cr unu---uuuuu 170326e20070301xx s 000 0 eng 10.1007/s10462-008-9087-0 doi (NATIONALLICENCE)springer-10.1007/s10462-008-9087-0 Recurrent neural robot controllers: feedback mechanisms for identifying environmental motion dynamics [Elektronische Daten] [Stephen McKibbin, Bala Amavasai, Arul Selvan, Fabio Caparrelli, W. Othman] In this paper a series of recurrent controllers for mobile robots have been developed. The system combines the iterative learning capability of neural controllers and the optimisation ability of particle swarms. In particular, three controllers have been developed: an Exo-sensing, an Ego-sensing and a Composite controller which is the hybrid of the latter two. The task for each controller is to learn to follow a moving target and identify its trajectory using only local information. We show how the learned behaviours of each architecture rely on different sensory representations, although good results are obtained in all cases. Springer Science+Business Media B.V., 2008 Dynamic Neural Networks nationallicence Particle Swarm Optimisation nationallicence Sensory-Motor Coordination nationallicence McKibbin Stephen Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut Amavasai Bala Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut Selvan Arul Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut Caparrelli Fabio Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut Othman W. Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut Artificial Intelligence Review Springer Netherlands 27/2-3(2007-03-01), 113-130 0269-2821 27:2-3<113 2007 27 10462 https://doi.org/10.1007/s10462-008-9087-0 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10462-008-9087-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- McKibbin Stephen Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut NATIONALLICENCE 700 1- Amavasai Bala Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut NATIONALLICENCE 700 1- Selvan Arul Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut NATIONALLICENCE 700 1- Caparrelli Fabio Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut NATIONALLICENCE 700 1- Othman W. Microsystems & Machine Vision Laboratory, Materials & Engineering Research Institute, Sheffield Hallam University, S1 1WB, Sheffield, UK aut NATIONALLICENCE 773 0- Artificial Intelligence Review Springer Netherlands 27/2-3(2007-03-01), 113-130 0269-2821 27:2-3<113 2007 27 10462 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer