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Abstract: humanoid robots represent a rapidly evolving research domain that integrates artificial intelligence and robotics. Despite significant advances, existing reviews have predominantly focused on narrow technical aspects and lack comprehensive analysis from both academic and industrial perspectives. This paper presents a systematic dual-perspective survey, in which academic literature, commercial products, and industry reports are extensively analyzed. A comprehensive taxonomic framework and systematic review key enabling technologies are established, including ontological structures, perception systems, locomotion control, intelligent decision-making algorithms, foundation model integration, and human-robot interaction (HRI) technologies. From academic and industrial perspectives, research progress across diverse applications is examined and a detailed comparative analysis of commercial products from leading companies, including Tesla, Boston Dynamics, and UBTECH, is performed. Six major challenge categories are identified: hardware design limitations, control system complexities, perception constraints, HRI difficulties, application-specific requirements, and ethical considerations. In addition, the transformative impact and integration challenges of large language models are particularly discussed.Seven promising research directions are outlined, and systematic academic-industrial gap analysis is conducted. Consequently, significant disparities and technology transfer bottlenecks are identified, and successful collaboration models are examined. This comprehensive survey provides the first systematic examination combining academic research insights with industrial development analysis. It thus offers valuable guidance for researchers, engineers, and policymakers working toward more capable, affordable, and socially integrated humanoid robots.