Data-driven autonomous robotic food handling

数据驱动的自主食品处理机器人

• 批准号: 2736888
• 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: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2736888
• 关键词: Data; driven; autonomous; robotic; food

The project will develop new reliable data-driven control algorithms for robotic manipulation. Technologies for low-cost handling of food products will be explored in this project. Some low-cost articulated robotic arms equipped with grasping end-effectors will be developed and tested with the reasonable speed, accuracy, and reliability.The research will focus on reliable data-driven control algorithms for food manipulation. The student will develop adaptive impedance control through a path of increasing complexity, starting from basic energy-aware control algorithms to a reliable adaptive control framework. This will be paired with mechanical design and prototyping, with the goal of co-designing control algorithms and (compliant, tuneable) hardware. The research will be validated on a commercial robotic system provided by RT Corp.The student will have full access to all teaching courses at undergraduate, master, and PhD level, in engineering and wider domains (communication, management, etc.). The student will also learn from a large body of activities at the Control Laboratory, at the Bio-Inspired Robotic Laboratory, and at the Observatory for Human-Machine Collaboration.

该项目将为机器人操作开发新的可靠的数据驱动控制算法。该项目将探索低成本处理食品的技术。将开发一些配备抓取末端执行器的低成本关节机械臂，并对其进行合理的速度、精度和可靠性测试。研究将集中在用于食品操纵的可靠的数据驱动控制算法。学生将通过一条日益复杂的途径来开发自适应阻抗控制，从基本的能源感知控制算法到可靠的自适应控制框架。这将与机械设计和原型设计相结合，目标是共同设计控制算法和(兼容的、可调的)硬件。这项研究将在RT公司提供的商业机器人系统上进行验证。学生将完全可以访问所有本科、硕士和博士级别的教学课程，在工程和更广泛的领域(通信、管理等)。学生还将从控制实验室、仿生机器人实验室和人机协作观察站的大量活动中学习。