DEFCOBOT (Design for Control of Flexible Robots)

DEFCOBOT（灵活机器人控制设计）

基本信息

批准号：
EP/R009708/1
负责人：
Ferdinando Rodriguez Y Baena
金额：
$ 30.51万
依托单位：
Imperial College London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FR009708%2F1
关键词：
DEFCOBOT Design Control Flexible Robots

项目摘要

Flexible robots have light and compliant bodies that allow them to adapt well to unstructured environments. However, due to their deformability, controlling their movements accurately in the presence of disturbances is a challenging task. Additionally, the design and manufacturing of flexible robots is generally conducted without prior analysis of their dynamic performance and involves refinements through successive prototypes. These factors reduce the accuracy and effectiveness of flexible robots in real-world applications, including surgery, inspection and maintenance. Finally, bespoke design and control solutions confine advances in these areas to specific cases. This research aims to produce advanced control methods and design guidelines for different types of flexible robots in order to enhance their performance. To demonstrate the general validity of the proposed methods we have chosen two illustrative applications from our own track record: robot-assisted biopsy and robotic inspection. In the experimental part of the project, the control methods will be validated with two proof-of-concept prototypes from our recent work that are representative of each application. Successful completion of this research will contribute to enhancing the accuracy and effectiveness of flexible robots which is an essential prerequisite for their wider use. Potential applications of the research findings include minimally-invasive robotic surgery, robotic inspection and maintenance.

灵活的机器人具有轻巧和兼容的身体，使它们可以很好地适应非结构化的环境。但是，由于它们的可变形性，在出现干扰的情况下准确控制其运动是一项艰巨的任务。此外，通常在没有先前分析其动态性能的情况下进行柔性机器人的设计和制造，并通过连续的原型进行改进。这些因素降低了在现实世界应用中的灵活机器人的准确性和有效性，包括手术，检查和维护。最后，定制的设计和控制解决方案将这些领域的进步局限于特定情况。这项研究旨在为不同类型的灵活机器人生成高级控制方法和设计指南，以提高其性能。为了证明所提出方法的一般有效性，我们从我们自己的往绩记录中选择了两个说明性应用：机器人辅助活检和机器人检查。在项目的实验部分中，控制方法将通过我们最近的工作代表每个应用程序的两个概念验证原型进行验证。这项研究的成功完成将有助于提高灵活机器人的准确性和有效性，这是其更广泛使用的必要先决条件。研究结果的潜在应用包括微创的机器人手术，机器人检查和维护。