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). While we adopt NICO's head and facial expression display, we extend 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：能够高效与人协作完成物理任务的机器人平台是机器人领域的核心目标之一。然而，现有机器人平台的设计多侧重于社交交互或工业物体操作中的单一功能。协作型机器人的设计鲜少同时强调其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）。作为经充分验证的前代机器人——神经启发式伙伴（NICO）——的升级放大版本，NICOL继承了NICO的头部与面部表情显示系统，但在操作精度、可操作物体尺寸及工作空间范围方面实现了能力扩展。为介绍并评估NICOL，我们首先将原本为NICO开发的多种神经及混合神经-基因视觉运动方法迁移至体型更大、运动学更复杂的NICOL平台。进一步地，我们提出了一种新型神经-基因方法，使NICOL的抓取成功率提升至99%以上，超越了业界领先的逆运动学求解器KDL、TRACK-IK和BIO-IK。此外，我们介绍了NICOL的社交交互能力，涵盖听觉与视觉感知功能，以及面部表情与情感生成机制。本文首次完整呈现了人形机器人NICOL及其神经-基因方法体系，为推动社交机器人与人形机器人神经视觉运动学习的融合做出了贡献。