Skip to main navigation Skip to search Skip to main content

Motion planning with worker's trajectory prediction for assembly task partner robot

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

We have developed a novel assembly task partner robot to support workers in their task. This system, PaDY (in-time Parts/tools Delivery to You robot), delivers parts and tools to a worker by recognizing the worker's behavior in the car production line; thus, improving the efficiency of the work by reducing the worker's physical workload for picking parts and tools. For this purpose, it is necessary to plan the trajectory of the robot before the worker moves to the next location for another assembling task. First a prediction method for the worker's trajectory using a Markov model for a discretized work space into cells is proposed, then motion planning method is proposed using the predicted worker's trajectory and a mixture Gaussian distribution for each area corresponding to each procedure of the work process in the automobile coordinate system. Experimental results illustrate the validity of the proposed motion planning method. © 2012 IEEE.
Original languageEnglish
Title of host publication2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012
Pages1525-1532
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012 - Vilamoura, Algarve, Portugal
Duration: 7 Oct 2012 → 12 Oct 2012
https://ieeexplore.ieee.org/xpl/conhome/6363628/proceeding

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012
PlacePortugal
CityVilamoura, Algarve
Period7/10/12 → 12/10/12
Internet address

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Fingerprint

Dive into the research topics of 'Motion planning with worker's trajectory prediction for assembly task partner robot'. Together they form a unique fingerprint.

Cite this