Passively Adaptive Robotic Hands: A Trade-off-driven Review of Core Mechanisms, Performance Indicators, and Application Scenarios

Abstract

Passively adaptive robotic hands have attracted growing attention because they shift part of the burden of grasp adaptation from sensing and control to mechanical design. However, existing reviews often discuss variable stiffness, underactuation, structural deformation, and related strategies separately, making it difficult to compare how different passive mechanisms balance adaptability, load capacity, grasp precision, and control simplicity. This paper provides a trade-off-driven and application-oriented review of passively adaptive robotic hands. The field is synthesized from a mechanism-performance-application perspective, covering four major categories: variable-stiffness mechanisms, underactuated coupling and transmission mechanisms, structural deformation mechanisms, and mode-switching and hybrid actuation strategies. These mechanisms are discussed in relation to key performance indicators, including shape adaptability, payload, positional tolerance, impact resistance, lightweight design, and reliability, as well as their relevance to representative scenarios such as daily object grasping, high-load manipulation, and clinical assistive applications. Rather than maximizing any single performance metric, passive adaptive mechanisms primarily contribute by redistributing competing design constraints through mechanical intelligence. Finally, this paper highlights current challenges, discusses limitations in cross-study performance comparison, and outlines promising directions for future research.