Towards Robotic Dexterous Hand Intelligence: A Survey
Weiguang Zhao, Tian Liang, Xihao Guo, Rui Zhang, Irwin King, Kaizhu Huang

TL;DR
This survey comprehensively reviews the hardware, control methods, data practices, and evaluation protocols in robotic dexterous hand research, highlighting challenges and future directions.
Contribution
It offers a holistic, structured overview connecting hardware, methodology, data, and evaluation to clarify the field's development and open challenges.
Findings
Analyzes key trade-offs in dexterous hand hardware design.
Reviews evolution of control and learning methods.
Summarizes datasets and evaluation practices.
Abstract
Robotic dexterous hands are central to contact-rich manipulation, with rapid progress driven by advances in hardware, sensing, control, simulation, and data generation. However, existing studies are often developed under different assumptions regarding hand embodiments, sensory configurations, task settings, training data, and evaluation protocols, making systematic comparison difficult and obscuring the developmental trajectory of the field. This survey provides a holistic review of dexterous hand research from four complementary aspects. First, we present a hardware-level analysis covering actuation, transmission, perception, and representative hand designs, highlighting the key trade-offs in force capability, compliance, bandwidth, integration, and system complexity. Furthermore, we review control and learning methods for dexterous manipulation from a methodological perspective,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
