自动设计能抓多种物体的肌腱驱动夹爪，无需复杂算法
Synergizing Morphological Computation and Generative Design: Automatic Synthesis of Tendon-Driven Grippers
- 用图语法和启发式搜索生成机械结构
- 自动生成的夹爪可抓取多种物体，性能稳定
- 适合机器人硬件设计初学者与自动化流程研究者
机器人的行为与性能由软硬件共同决定。机器人系统的设计过程复杂且需兼顾多重矛盾目标。本文提出一种生成式设计方法，用于构建具有形态计算能力的机器人连杆机构。通过图语法与启发式搜索生成机械结构图，并转化为仿真模型进行测试。针对静态抓取任务验证该方法，成功自动设计出一种欠驱动肌腱驱动夹爪，可在无复杂规划或学习的情况下稳定抓取多种物体，其性能源于结构本身而非控制策略。
原文摘要 · Abstract (English)
Robots' behavior and performance are determined both by hardware and software. The design process of robotic systems is a complex journey that involves multiple phases. Throughout this process, the aim is to tackle various criteria simultaneously, even though they often contradict each other. The ultimate goal is to uncover the optimal solution that resolves these conflicting factors. Generative, computation or automatic designs are the paradigms aimed at accelerating the whole design process. Within this paper we propose a design methodology to generate linkage mechanisms for robots with morphological computation. We use a graph grammar and a heuristic search algorithm to create robot mechanism graphs that are converted into simulation models for testing the design output. To verify the design methodology we have applied it to a relatively simple quasi-static problem of object grasping. We found a way to automatically design an underactuated tendon-driven gripper that can grasp a wide range of objects. This is possible because of its structure, not because of sophisticated planning or learning.
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