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. To introduce and evaluate NICOL, we first develop and extend different neural and hybrid neuro-genetic visuomotor approaches initially developed for the NICO to the larger NICOL and its more complex kinematics. Furthermore, we present a novel neuro-genetic approach that improves the grasp-accuracy of the NICOL to over 99%, outperforming the state-of-the-art IK solvers KDL, TRACK-IK and BIO-IK. Furthermore, we introduce the social interaction capabilities of NICOL, including the auditory and visual capabilities, but also the face and emotion generation capabilities. Overall, this article presents for the first time the humanoid robot NICOL and, thereby, with the neuro-genetic approaches, contributes to the integration of social robotics and neural visuomotor learning for humanoid robots.

翻译：在物理任务中与人类高效协作的机器人平台是机器人学的主要目标之一。然而，许多现有机器人平台要么专为社交交互设计，要么专为工业物体操作任务设计。协作型机器人的设计鲜少同时强调社交交互与物理协作能力。为弥合这一鸿沟，我们提出了新型半人形机器人NICOL（神经启发式协作者）。NICOL是经过充分验证的前代机器人——神经启发式伙伴（NICO）——的全新升级放大版，继承了NICO的头部结构与面部表情显示功能，并在操作精度、物体尺寸与工作空间范围方面扩展了操控能力。为介绍并评估NICOL，我们首先将最初为NICO开发的多种神经方法与混合神经基因视觉运动方法适配至更大型的NICOL及其更复杂的运动学系统。此外，我们提出了一种新型神经基因方法，使NICOL的抓取精度提升至99%以上，超越当前最优逆运动学求解器KDL、TRACK-IK与BIO-IK。同时，我们展示了NICOL的社交交互能力，包括听觉与视觉功能，以及面部表情与情绪生成能力。总体而言，本文首次完整呈现人形机器人NICOL，并通过神经基因方法，为社交机器人技术与人形机器人神经视觉运动学习的整合做出了贡献。