title: Modeling human target reaching with an adaptive observer implemented with dynamic neural fields.
abstract: Humans can point fairly accurately to memorized states when closing their eyes despite slow or even missing sensory feedback. It is also common that the arm dynamics changes during development or from injuries. We propose a biologically motivated implementation of an arm controller that includes an adaptive observer. Our implementation is based on the neural field framework, and we show how a path integration mechanism can be trained from few examples. Our results illustrate successful generalization of path integration with a dynamic neural field by which the robotic arm can move in arbitrary directions and velocities. Also, by adapting the strength of the motor effect the observer implicitly learns to compensate an image acquisition delay in the sensory system. Our dynamic implementation of an observer successfully guides the arm toward the target in the dark, and the model produces movements with a bell-shaped velocity profile, consistent with human behavior data.
authors.affiliation: Faculty of Computer Science, Dalhousie University, NS, Canada. Electronic address: fard@cs.dal.ca.
authors.forename: Farzaneh S
authors.initials: FS
authors.lastname: Fard
authors.affiliation: Faculty of Computer Science, Dalhousie University, NS, Canada. Electronic address: hollense@cs.dal.ca.
authors.forename: Paul
authors.initials: P
authors.lastname: Hollensen
authors.affiliation: Center for Computational Neuroscience and Cognitive Robotics, School of Psychology, University of Birmingham, UK. Electronic address: d.g.heinke@bham.ac.uk.
authors.forename: Dietmar
authors.initials: D
authors.lastname: Heinke
authors.affiliation: Faculty of Computer Science, Dalhousie University, NS, Canada. Electronic address: tt@cs.dal.ca.
authors.forename: Thomas P
authors.initials: TP
authors.lastname: Trappenberg
mesh_terms: D001132:Arm; D001921:Brain / Q000502:physiology*; D006801:Humans; D007858:Learning; D008959:Models, Neurological; D009068:Movement / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology*; D012371:Robotics
keywords: Adaptive controller; Dynamic neural fields; Internal model; Observer; Path integration; Target reaching