Zhu Yicheng, Yang David, Lee Yangming
RoCAL Laboratory, Rochester Institute of Technology, Rochester, NY 14623, USA.
Sensors (Basel). 2025 Sep 2;25(17):5430. doi: 10.3390/s25175430.
Deformable object manipulation (DOM) is a primary bottleneck for the real-world application of autonomous robots, requiring advanced frameworks for sensing, perception, modeling, planning, and control. When fragile objects such as soft tissues or fruits are involved, ensuring safety becomes the paramount concern, fundamentally altering the manipulation problem from one of pure trajectory optimization to one of constrained optimization and real-time adaptive control. Existing DOM methodologies, however, often fall short of addressing fragility constraints as a core design feature, leading to significant gaps in real-time adaptiveness and generalization. This review systematically examines individual components in DOM with a focus on their effectiveness in handling fragile objects. We identified key limitations in current approaches and, based on this analysis, discussed a promising framework that utilizes both low-latency reflexive mechanisms and global optimization to dynamically adapt to specific object instances.
可变形物体操纵(DOM)是自主机器人在现实世界应用中的一个主要瓶颈,需要先进的传感、感知、建模、规划和控制框架。当涉及到诸如软组织或水果等易碎物体时,确保安全成为首要关注点,这从根本上改变了操纵问题,从单纯的轨迹优化问题转变为约束优化和实时自适应控制问题。然而,现有的DOM方法往往未能将易碎性约束作为核心设计特征加以解决,导致在实时适应性和通用性方面存在重大差距。本综述系统地研究了DOM中的各个组件,重点关注它们在处理易碎物体方面的有效性。我们确定了当前方法中的关键局限性,并在此分析的基础上,讨论了一个有前景的框架,该框架利用低延迟反射机制和全局优化来动态适应特定的物体实例。