Robotic competitions are an excellent way to promote innovative solutions for the current industries’ challenges and entrepreneurial spirit, acquire technical and transversal skills through active teaching, and promote this area to the public. In other words, since robotics is a multidisciplinary field, its competitions
address several knowledge topics, especially in the STEM (Science, Technology, Engineering, and Mathematics) category, that are shared among the students and researchers, driving further technology and science. A new competition encompassed in the Portuguese Robotics Open was created according to the
Industry 4.0 concept in the production chain. In this competition, RobotAtFactory 4.0, a shop floor, is used to mimic a fully automated industrial logistics warehouse and the challenges it brings. Autonomous Mobile Robots (AMRs) must be used to operate without supervision and perform the tasks that the warehouse requests. There are different types of boxes which dictate their partial and definitive destinations. In this reasoning, AMRs should identify each and transport them to their destinations. This paper
describes an approach to the indoor localization system for the competition based on the Extended Kalman Filter (EKF) and ArUco markers. Different innovation methods for the obtained observations were tested and
compared in the EKF. A real robot was designed and assembled to act as a test bed for the localization system’s validation. Thus, the approach was validated in the real scenario using a factory floor with the official
specifications provided by the competition organization.
The authors are grateful to the Foundation for Science and
Technology (FCT, Portugal) for financial support through
national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/
05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/
2021). The project that gave rise to these results received the
support of a fellowship from “la Caixa” Foundation (ID
100010434). The fellowship code is LCF/BQ/DI20/11780028.
The authors also acknowledge the R&D Unit SYSTEC-Base
(UIDB/00147/2020), Programmatic (UIDP/00147/2020) and
Project Warehouse of the Future (WoF), with reference
POCI-01-0247-FEDER-072638, co-funded by FEDER, through
COMPETE 2020
