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HumRobManip

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

Total Cost €

0

EC-Contrib. €

0

Partnership

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Project "HumRobManip" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITY OF LEEDS 

Organization address
address: WOODHOUSE LANE
city: LEEDS
postcode: LS2 9JT
website: www.leeds.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 195˙454 €
 EC max contribution 195˙454 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-RI
 Starting year 2017
 Duration (year-month-day) from 2017-05-01   to  2019-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITY OF LEEDS UK (LEEDS) coordinator 195˙454.00

Map

 Project objective

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.

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The information about "HUMROBMANIP" are provided by the European Opendata Portal: CORDIS opendata.

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