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.
Humanoid Locomotion with a Fly-Inspired Recurrent Controller
The Hong Kong University of Science and Technology（香港科技大学）；Zenbot；Nanyang Technological University（南洋理工大学）；The Hong Kong Polytechnic University（香港理工大学）
Shaken, Not Stirred: A Novel Dataset for Visual Understanding of Glasses in Human-Robot Bartending Tasks
Department of Applied Informatics, Faculty of Mathematics, Physics and Informatics, Comenius University（应用信息学院，数学物理学院，科门ius大学）；Knowledge Technology Group, Department of Informatics, University of Hamburg（知识技术组，信息学院，汉堡大学）
Bayesian Optimization Using Domain Knowledge on the ATRIAS Biped
Robotics Institute, School of Computer Science, Carnegie Mellon University（卡内基梅隆大学计算机科学学院机器人研究所）；Robotics, Perception and Learning, CSC, KTH Royal Institute of Technology（瑞典皇家理工学院计算机科学与通信系机器人、感知与学习部门）
Emotive Response to a Hybrid-Face Robot and Translation to Consumer Social Robots
Imperial College London（帝国理工学院）；UK Dementia Research Institute（英国痴呆症研究所）；University of Bristol（布里斯托尔大学）；University of Warwick（华威大学）；Emotix Inc（Emotix公司）
A Hybrid Deep Learning Framework for Emotion Recognition in Children with Autism During NAO Robot-Mediated Interaction
Department of Information Technology, School of Engineering, Cochin University of Science and Technology（科钦大学科学与技术学院信息科技系）；Indian Institute of Technology Kanpur（印度理工学院坎普尔学院）
