Planning, control and learning for intelligent robotic manipulation

智能机器人操纵的规划、控制和学习

• 批准号: 1949457
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 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=studentship-1949457
• 关键词: Planning; control; learning; intelligent; robotic

This project will develop intelligent robotic algorithms and systems for object manipulation tasks. Example tasks include a robot reaching into a cluttered shelf to grasp objects and a robot using tools to cut and drill objects) Particular topics include: Manipulation planning using physics-based predictions of object motion, Machine learning for manipulation planning and control, Manipulation based on tactile sensing (e.g. artificial skin), Multi-robot collaborative manipulation, Human-robot collaborative manipulation, and Manipulation planning for flexible manufacturing and assembly.

该项目将开发用于对象操作任务的智能机器人算法和系统。示例任务包括机器人伸入杂乱的架子中抓取物体，以及机器人使用工具切割和钻孔物体）具体主题包括：使用基于物理的物体运动预测进行操纵规划、用于操纵规划和控制的机器学习、基于触觉感知的操纵（例如人造皮肤）、多机器人协作操纵、人机协作操纵以及用于灵活制造和装配的操纵规划。

项目成果

Non-Prehensile Manipulation in Clutter with Human-In-The-Loop

通过人在环在混乱中进行非预先操纵

• 发表时间: 2020
• 作者: Papallas R

Online Replanning With Human-in-the-Loop for Non-Prehensile Manipulation in Clutter - A Trajectory Optimization Based Approach

利用人在环进行在线重新规划，实现杂波中的非预先操纵 - 一种基于轨迹优化的方法

• DOI: 10.1109/lra.2020.3006826
• 发表时间: 2020
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Papallas R