Towards a Unified Understanding of Robot Manipulation: A Comprehensive Survey

[2510.10903] Towards a Unified Understanding of Robot Manipulation: A Comprehensive Survey Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Robotics arXiv:2510.10903 (cs) [Submitted on 13 Oct 2025 ( v1 ), last revised 15 Aug 2026 (this version, v2)] Title: Towards a Unified Understanding of Robot Manipulation: A Comprehensive Survey Authors: Shuanghao Bai , Wenxuan Song , Jiayi Chen , Yuheng Ji , Zhide Zhong , Jin Yang , Han Zhao , Wanqi Zhou , Wei Zhao , Zhe Li , Pengxiang Ding , Cheng Chi , Haoang Li , Chang Xu , Xiaolong Zheng , Donglin Wang , Shanghang Zhang , Badong Chen View a PDF of the paper titled Towards a Unified Understanding of Robot Manipulation: A Comprehensive Survey, by Shuanghao Bai and 17 other authors View PDF HTML (experimental) Abstract: Embodied intelligence has witnessed remarkable progress in recent years, driven by advances in computer vision, natural language processing, and the rise of large-scale multimodal models. Among its core challenges, robot manipulation stands out as a fundamental yet intricate problem, requiring the seamless integration of perception, planning, and control to enable interaction within diverse and unstructured environments. This survey presents a comprehensive overview of robotic manipulation, encompassing foundational background, task-organized benchmarks and datasets, and a unified taxonomy of existing methods. We extend the classical division between high-level planning and low-level control by broadening high-level planning to include language, code, motion, affordance, and 3D representations, while introducing a new taxonomy of low-level learning-based control grounded in training paradigms such as input modeling, latent learning, and policy learning. Furthermore, we provide the first dedicated taxonomy of key bottlenecks, focusing on data collection, utilization, and generalization, and conclude with an extensive review of real-world applications. Compared with prior surveys, our work offers both a broader scope and deeper insight, serving as an accessible roadmap for newcomers and a structured reference for experienced researchers. All related resources, including research papers, open-source datasets, and projects, are curated for the community at this https URL . Subjects: Robotics (cs.RO) Cite as: arXiv:2510.10903 [cs.RO] (or arXiv:2510.10903v2 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2510.10903 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Shuanghao Bai [ view email ] [v1] Mon, 13 Oct 2025 01:59:27 UTC (13,504 KB) [v2] Sat, 15 Aug 2026 10:43:36 UTC (15,248 KB) Full-text links: Access Paper: View a PDF of the paper titled Towards a Unified Understanding of Robot Manipulation: A Comprehensive Survey, by Shuanghao Bai and 17 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.RO < prev | next > new | recent | 2025-10 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... 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