H2020Индивидуална стипендия2017–2019

HumRobManip · Robotic Manipulation Planning for Human-Robot Collaboration on Forceful Manufacturing Tasks

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2017-05-01 → 2019-04-30
Финансиране от ЕС: 195 455 €
Участници: 1
Схема: MSCA-IF-EF-RI

Линиите свързват координатора с партньорите.

Накратко на български

Роботизираното планиране на движенията позволява на машината да държи стабилно обект, докато човек извършва дейности като пробиване на дупки или рязане. Това помага за създаването на системи, при които хора и роботи работят заедно в производствената среда, вместо да бъдат разделени.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Robotic Manipulation Planning for Human-Robot Collaboration on Forceful Manufacturing Tasks

This project focused on robotic manipulation planning for human-robot interaction during forceful collaboration. Take the example where a human is drilling holes onto a board and then cutting a piece of it. As the human applies the operations, the robot grasps the board for the human, occasionally changing its grasp on the object, always trying to maximize the stability and smoothness of the interaction. The project addressed various technical challenges associated with this problem. First, it addressed the algorithmic challenge of planning a sequence of grasps for multiple manipulators (e.g. a robot with two arms). Second, it addressed the problem of modelling of the human forces applied during the interaction. Third, it addressed the problem of human body posture during the interaction. Finally, it addressed the problem of integrating these algorithms on a real robot system. The project resulted in algorithms and systems that go beyond the state of the art in addressing these challenges. Particularly, in terms of taking a manipulation planning approach to the problem of human-robot forceful collaboration, to the best of our knowledge, this project generated the first set of algorithms in the literature. The project also resulted in creating new collaborations between myself and the School of Biomedical Sciences at the University of Leeds. In today’s factory automation, robots and humans work separated from each other, making it impossible for them to collaborate and complement each other’s skills. This project developed algorithms which enable human-robot collaboration in manufacturing environments, a key manufacturing technology for the future of Europe.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

This proposal addresses robotic manipulation planning for human-robot collaboration during manufacturing. My objective is to develop a planning framework which will enable a team of robots to grasp, move and position manufacturing parts (e.g. planks of wood) such that a human can execute sequential forceful manufacturing operations (e.g. drilling, cutting) to build a product (e.g. a wooden table). The overall objective is divided into three components: First, I will develop a planning algorithm which, given the description of a manufacturing task, plans the actions of all robots in a human-robot team to perform the task. Second, I will develop probabilistic models of human interaction to be used by the planner. This model will include (i) an action model that assigns probabilities to different manufacturing operations (e.g. drilling a hole vs. cutting a piece off) as the next actions the human intends to do; (ii) a geometric model that assigns probabilities to human body postures; and (iii) a force model that assigns probabilities to force vectors as the predicted operational forces. Third, I will build a real robotic system to perform experiments and test my algorithm's capabilities. This system will consist of at least three robot manipulators.This fellowship will enable me to add a completely new human dimension to my planning research. I will work with Prof. Tony Cohn (supervisor) who is a world-leading expert in human activity recognition and prediction - a critical skill for the human-robot collaboration problem I intend to solve. From him and his group, I will receive training on tracking/predicting human posture and recognizing/predicting human activities using vision and point-cloud data. I will then integrate these tracking and prediction methods into a robotic planning framework to enable human-robot collaborative operations. This fellowship will help me to attain a permanent academic position and to become a leading researcher in robotic manipulation.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSITY OF LEEDS · LeedsКоординаторОбединеното кралство