Accurate control of a low-cost soft robotic arm for automated strawberry picking (Ref: CTP_FCR_2020_5)

精确控制低成本软机械臂，用于自动化草莓采摘（参考：CTP_FCR_2020_5）

• 批准号: 2476449
• 金额: --
• 依托单位: University of Lincoln
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2476449
• 关键词: Accurate; control; low; cost; soft

This student is to be registered with University of Lincoln and will be mainly based in the University. The team of supervisors includes Prof Gerhard Neuman (University of Lincoln), Dr Khaled Elgeneidy (University of Lincoln), and Dr Bo Li (NIAB)The PhD student will work on the development and control of a bespoke soft arm targeted at the strawberry picking application. This is expected to involve embedding of customised flexible sensors to provide additional positional feedback so that accurate closed-loop control can be achieved. The design of the soft arm will consider the potential for delivering picked strawberries to the robot base by utilising an internal passage through the soft arm, to reduce the need for moving the arm back to the base after each pick and hence shortening the picking cycle. The soft arm body can be potentially 3D printed from flexible materials to automate the fabrication process and yield a more consistent output. Machine learning algorithms will be investigated for online learning control for the soft arm, such that variations from the soft materials and fabrication process can be effectively accounted for using experimental data.

该学生将在林肯大学注册，并将主要在该大学工作。导师团队包括Gerhard Neuman教授（林肯大学）、Khaled Elgeneidy博士（林肯大学）和Bo Li博士（NIAB）。博士生将致力于开发和控制针对草莓采摘应用的定制软臂。预计这将涉及嵌入定制的柔性传感器，以提供额外的位置反馈，从而实现精确的闭环控制。软臂的设计将考虑通过利用穿过软臂的内部通道将采摘的草莓输送到机器人基座的可能性，以减少每次采摘后将臂移回基座的需要，从而缩短采摘周期。软臂主体可以由柔性材料3D打印，以自动化制造过程并产生更一致的输出。机器学习算法将被研究用于软臂的在线学习控制，使得可以使用实验数据有效地解释软材料和制造过程的变化。