  Robotic platforms that can efficiently collaborate with humans in physical
tasks constitute a major goal in robotics. However, many existing robotic
platforms are either designed for social interaction or industrial object
manipulation tasks. The design of collaborative robots seldom emphasizes both
their social interaction and physical collaboration abilities. To bridge this
gap, we present the novel semi-humanoid NICOL, the Neuro-Inspired COLlaborator.
NICOL is a large, newly designed, scaled-up version of its well-evaluated
predecessor, the Neuro-Inspired COmpanion (NICO). NICOL adopts NICO's head and
facial expression display and extends its manipulation abilities in terms of
precision, object size, and workspace size. Our contribution in this paper is
twofold -- firstly, we introduce the design concept for NICOL, and secondly, we
provide an evaluation of NICOL's manipulation abilities by presenting a novel
extension for an end-to-end hybrid neuro-genetic visuomotor learning approach
adapted to NICOL's more complex kinematics. We show that the approach
outperforms the state-of-the-art Inverse Kinematics (IK) solvers KDL, TRACK-IK
and BIO-IK. Overall, this article presents for the first time the humanoid
robot NICOL, and contributes to the integration of social robotics and neural
visuomotor learning for humanoid robots.
