Open this publication in new window or tab >>2014 (English)In: Proceedings of the 19th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA'14), Barcelona, Spain, September, 2014, 2014, p. Article number 7005148-Conference paper, Published paper (Refereed)
Abstract [en]
In this paper, scheduling of robot cells that produce multiple object types in low volumes are considered. The challenge is to maximize the number of objects produced in a given time window as well as to adopt the schedule for changing object types. Proposed algorithm, POPStar, is based on a partial order planner which is guided by best-first search algorithm and landmarks. The best-first search, uses heuristics to help the planner to create complete plans while minimizing the makespan. The algorithm takes landmarks, which are extracted from user's instructions given in structured English as input. Using different topologies for the landmark graphs, we show that it is possible to create schedules for changing object types, which will be processed in different stages in the robot cell. Results show that the POPStar algorithm can create and adapt schedules for robot cells with changing product types in low volume production.
National Category
Robotics
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-26465 (URN)10.1109/ETFA.2014.7005148 (DOI)000360999100099 ()2-s2.0-84946692437 (Scopus ID)978-147994846-8 (ISBN)
Conference
19th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA'14), Barcelona, Spain, 16-19 September, 2014
2014-11-052014-11-052016-01-18Bibliographically approved