Details
Name
Marina BrilhanteRole
Research AssistantSince
03rd October 2022
Nationality
PortugalCentre
Robotics in Industry and Intelligent SystemsContacts
+351222094353
marina.brilhante@inesctec.pt
2024
Authors
Brilhante, M; Rebelo, PM; Oliveira, PM; Sobreira, H; Costa, P;
Publication
ROBOT 2023: SIXTH IBERIAN ROBOTICS CONFERENCE ADVANCES IN ROBOTICS, VOL 1
Abstract
Since creating universally capable robots is challenging for a single manufacturer, a diverse fleet of robots from various manufacturers is utilized. However, these heterogeneous fleets encounter communication and interoperability issues. As a result, there is a growing need for a standardized interface that is capable of communicating, controlling and managing a diverse fleet without these interoperability issues. This paper presents a translation software module capable of controlling an autonomous mobile robot and communicating with a ROS-based robot fleet manager using the VDA5050 Standard and exchanging information via the MQTT communication protocol, aiming at flexibility and control across different robot brands. The effectiveness of the software in controlling a mobile robot via the VDA5050 standard was demonstrated by the results. It accurately analysed data from the Robot Fleet Manager, converted it into VDA 5050 JSON messages and skilfully translated it back into ROS messages. The robot's behavior remained consistent before and after the VDA5050 implementation.
2024
Authors
Silva, RT; Brilhante, M; Sobreira, H; Matos, D; Costa, P;
Publication
2024 7th Iberian Robotics Conference, ROBOT 2024
Abstract
Autonomous Mobile Robots (AMRs) and Automated Guided Vehicles (AGVs) have emerged as key innovations in the industry world, with AMRs offering flexibility a nd adaptability for dynamic environments, while AGVs provide high accuracy for repetitive tasks; thus, this research proposes a study of fleets of both AGVs and AMRs to enhance productivity and efficiency in industrial settings. Several tests were performed where the duration of a mission, the success and collision rate, and the average number of disputes per mission were analyzed in order to obtain results. In conclusion, while AGVs tend to be more reliable and consistent in task completion, AMRs offer greater flexibility a nd speed. © 2024 IEEE.
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