Key Takeaways & Executive Findings
- •• This is the first systematic review combining academic research insights with industrial development analysis for humanoid robots. • A comprehensive taxonomic framework and review of key enabling technologies (perception, control, decision-making, HRI, foundation models) are established. • Comparative analysis of commercial products from Tesla, Boston Dynamics, and UBTECH reveals significant disparities and technology transfer bottlenecks. • Six major challenge categories and seven future research directions are identified, emphasizing the integration of large language models.
Abstract
Humanoid robotics represents 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 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 of 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 a 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.
1. Introduction
Humanoid robotics, also known as anthropomorphic or human-like robots, represents a significant research branch within intelligent robotics that has witnessed unprecedented growth in recent years. In general, humanoid robots possess human-like forms and functions, including anthropomorphic limbs, movement, and operational skills, as well as perception, learning, and cognitive abilities. They can perform complex or specific human-like activities in various environments, embodying a high degree of integration between artificial intelligence (AI) and robotics technologies. Compared with other types of intelligent robots, humanoid robots exhibit stronger environmental adaptability, perform more diverse task operations, and establish more harmonious human–robot interaction (HRI); thus, they are recognized as comprehensive embodiments of robotic technologies.
The application domains of humanoid robots are expanding rapidly, with areas encompassing education, entertainment, service industries, healthcare, industrial production, disaster rescue, and military operations. With technological advancements driven by breakthroughs in AI, materials science, and manufacturing processes, humanoid robots are gradually transitioning from laboratory prototypes to practical assistants in human life and work. However, existing research and applications of humanoid robots, particularly those with high intelligence and commercial viability, face significant challenges that demand systematic analysis and strategic solutions. Recent advances in AI, particularly the emergence of large language models (LLMs) and foundation models, have provided new impetus for addressing these challenges and expanding the capabilities of humanoid robots. The integration of sophisticated natural language understanding with embodied intelligence represents a paradigm shift toward more intuitive HRI; however, it has introduced new technical and safety considerations that require systematic investigations.
Despite the growing interest in humanoid robotics, existing literature reviews exhibit several critical limitations that are addressed in this paper. Most previous sur...
Loading authentic research manuscript (Pages 1–5)...
Wenjuan LI, Genyuan YANG, Jiyi WU, Chengjie PAN, Lei SHENG, Qifei ZHANG (2025). A comprehensive review on humanoid robots: perspectives from academia and industry. Frontiers of Information Technology & Electronic Engineering. https://doi.org/10.1631/ENG_ITEE_2025_0105
Research & Educational Purpose Only:The translations, structured abstracts, analytical annotations, and data reports provided by SinoTechIntel are intended exclusively for academic research, internal corporate R&D, and educational benchmarking. They do not constitute formal engineering, chemical safety, legal, or professional advice.
Copyright & Intellectual Property Notice: Original copyright of the underlying source articles and experimental data remains with the respective authors, institutions, and original publishing journals. SinoTechIntel claims intellectual property only over its proprietary translations, analytical syntheses, and AEO structured enhancements in accordance with international fair use and academic citation principles.
Frequently Asked Questions
What does this review cover?
It provides a systematic dual-perspective survey of humanoid robots, analyzing academic literature, commercial products, and industry reports to establish a comprehensive taxonomy and review of key enabling technologies.
Which companies are compared in the review?
Commercial products from leading companies including Tesla, Boston Dynamics, and UBTECH are comparatively analyzed.
What are the main challenges identified for humanoid robots?
Six major challenge categories are identified: hardware design limitations, control system complexities, perception constraints, human-robot interaction difficulties, application-specific requirements, and ethical considerations.
What future directions are proposed?
Seven promising research directions are outlined, with particular emphasis on integrating large language models and addressing academic-industrial technology transfer bottlenecks.
Who can benefit from this review?
Researchers, engineers, and policymakers working toward more capable, affordable, and socially integrated humanoid robots.
Related Technical Papers & Translations
Design and optimization of a high-efficiency distillation process for cellulosic fuel ethanol integrated with thermal coupling and molecular sieve adsorption
To address the challenges of high energy consumption and prominent costs in the traditional three-columns distillation process for cellulosic fuel ethanol, a distillation—molecular sieve coupling separation process is proposed. This process integrates a three-column (crude distillation column, first distillation column, second distillation column) system with a 3A molecular sieve adsorption deep dehydration unit. A thermal coupling network is constructed via differential pressure design (steam from medium/high-pressure columns as mutual heat sources, reboiler liquid waste heat for feed preheating), and molecular sieve adsorption conditions are optimized. The study first performs a thermodynamic consistency test on the ethanol—water system, determines optimal non-random two-liquid (NRTL) model binary interaction parameters via experimental data regression for Aspen Plus simulation. Aiming at minimum total annual cost (TAC), Aspen Plus is used to optimize process parameters (theoretical tray number, feed location, reflux ratio, side-draw position, etc.). Economic analysis shows this process reduces CO2 emission costs by 27.56%, TAC by 15.58% (to 5.123 × 106 USD·a-1), and increases ethanol purity to ＞99.6%, providing an effective solution for green, efficient separation.
A cohesion loss model for determining residual strength of deep bedded sandstone
Rock residual strength, as an important input parameter, plays an indispensable role in proposing the reasonable and scientific scheme about stope design, underground tunnel excavation and stability evaluation of deep chambers. Therefore, previous residual strength models of rocks established were reviewed. And corresponding related problems were stated. Subsequently, starting from the effects of bedding and whole life-cycle evolution process, series of triaxial mechanical tests of deep bedded s
Federated model with contrastive learning and adaptive control variates for human activity recognition
Recent attention to privacy issues demands a communication-safe method for training human activity recognition (HAR) models on client activity data. Federated learning (FL) has become a compelling technique to facilitate model training between the server and clients while preserving data privacy. However, classical FL methods often assume independent and identically distributed (IID) data among clients. This assumption does not hold true in practical scenarios. Human activity in real-world scena