Reconfigurable robotic modules for rapid design iteration of soft robot applications

可重构机器人模块，用于软机器人应用的快速设计迭代

• 批准号: 2109088
• 金额: --
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2109088
• 关键词: Reconfigurable; robotic; modules; rapid; design

Soft robotics is expected to provide significant impact in the future of human-friendly robotics applications such as wearable devices for elderly body support, rehabilitations, medical robots, and other service robot applications. However most of the robot components such as motors, sensors, and controllers exist only under the assumptions of rigid regime, and they are not desirable for unconventional soft systems. This project aims to establish a developmental framework of reconfigurable robotic modules that can significantly speed up the design iterations of soft robot applications. The reconfigurable robotic modules should be comparatively small and flexible, such that they can be quickly applied to many variations of soft mechatronics devices by employing rapid fabrication methods such as 3D Printing and silicon moulding. The modules should also be supported by a software library and/or middleware for rapid development of controllers. The developed framework will be used for the case study of developing dextrous robotic hands for manipulation of unknown/unstructured objects.

软机器人技术有望对人类友好的机器人应用程序的未来产生重大影响，例如用于老年人身体支持、康复、医疗机器人和其他服务机器人应用的可穿戴设备。然而，大多数机器人部件，如电机、传感器和控制器，都是在刚性体制的假设下存在的，对于非传统的软系统来说，它们是不可取的。该项目旨在建立一个可重构机器人模块的开发框架，以显著加快软机器人应用程序的设计迭代。可重构的机器人模块应该相对较小和灵活，以便它们可以通过采用3D打印和硅模压等快速制造方法快速应用于许多不同的软机电设备。模块还应由软件库和/或中间件支持，以便快速开发控制器。开发的框架将用于开发用于操作未知/非结构化对象的灵巧机器人手的案例研究。

项目成果

Suction Cup Based on Particle Jamming and Its Performance Comparison in Various Fruit Handling Tasks

基于颗粒干扰的吸盘及其在各种水果处理任务中的性能比较

• DOI: 10.1109/aim43001.2020.9158945
• 发表时间: 2020
• 作者: Gilday K

Predictive Learning of Error Recovery with a Sensorized Passivity-Based Soft Anthropomorphic Hand

使用基于传感无源性的软拟人手进行错误恢复的预测学习

• DOI: 10.1002/aisy.202200390
• 发表时间: 2023
• 期刊: Advanced Intelligent Systems
• 影响因子: 7.4
• 作者: Gilday K

Predictive Learning of Error Recovery with a Sensorised Passivity-based Soft Anthropomorphic Hand

使用基于传感被动的软拟人手进行错误恢复的预测学习

• DOI: 10.17863/cam.94540
• 发表时间: 2023
• 作者: Gilday K

Wrist-driven passive grasping: interaction-based trajectory adaption with a compliant anthropomorphic hand.

手腕驱动的被动抓取：使用顺从的拟人手进行基于交互的轨迹适应。

• DOI: 10.17863/cam.64374
• 发表时间: 2021
• 作者: Gilday K

Passivity-Based Hands Towards General-Purpose Robotic Manipulation

基于被动的手向通用机器人操作迈进

• DOI: 10.17863/cam.97062
• 发表时间: 2022
• 作者: Gilday K