Estrategias y tecnologías para la colaboración segura entre personas y robots en entornos industriales

383 p.En este trabajo se presentan diferentes contribuciones encaminadas a facilitar el desarrollo de soluciones robóticas colaborativas fáciles de usar, flexibles y seguras.Fáciles de usar mediante la utilización de tecnologías semánticas que permiten combinar dos mecanismos de interacción, los gestos y la voz, La contribución incluye, además, el desarrollo de la tecnología necesaria para el reconocimiento de gestos.La contribución en el campo de la seguridad se ha centrado en la definición de arquitecturas y estrategias de seguridad, así como en el desarrollo de tecnologías que permiten implementar el modo SSM: el seguimiento de personas y la monitorización de proximidad. Además se ha experimentado con potenciales usuarios de la robótica colaborativa para conocer el grado de aceptación de las diferentes tecnologías desarrolladas, tanto para la seguridad como para la interacción Finalmente se presentan las contribuciones encaminadas a dotar a los robots de capacidades de percepción que les doten de la flexibilidad necesaria para adaptarse a las condiciones cambiantes del entorno

Estrategias y tecnologías para la colaboración segura entre personas y robots en entornos industriales

383 p.En este trabajo se presentan diferentes contribuciones encaminadas a facilitar el desarrollo de soluciones robóticas colaborativas fáciles de usar, flexibles y seguras.Fáciles de usar mediante la utilización de tecnologías semánticas que permiten combinar dos mecanismos de interacción, los gestos y la voz, La contribución incluye, además, el desarrollo de la tecnología necesaria para el reconocimiento de gestos.La contribución en el campo de la seguridad se ha centrado en la definición de arquitecturas y estrategias de seguridad, así como en el desarrollo de tecnologías que permiten implementar el modo SSM: el seguimiento de personas y la monitorización de proximidad. Además se ha experimentado con potenciales usuarios de la robótica colaborativa para conocer el grado de aceptación de las diferentes tecnologías desarrolladas, tanto para la seguridad como para la interacción Finalmente se presentan las contribuciones encaminadas a dotar a los robots de capacidades de percepción que les doten de la flexibilidad necesaria para adaptarse a las condiciones cambiantes del entorno

Dynamic mosaic planning for a robotic bin-packing system based on picked part and target box monitoring

This paper describes the dynamic mosaic planning method developed in the context of the PICKPLACE European project. The dynamic planner has allowed the development of a robotic system capable of packing a wide variety of objects without having to adjust to each reference. The mosaic planning system consists of three modules: First, the picked item monitoring module monitors the grabbed item to find out how the robot has picked it. At the same time, the destination container is monitored online to obtain the actual status of the packaging. To this end, we present a novel heuristic algorithm that, based on the point cloud of the scene, estimates the empty volume inside the container as empty maximal spaces (EMS). Finally, we present the development of the dynamic IK-PAL mosaic planner that allows us to dynamically estimate the optimal packing pose considering both the status of the picked part and the estimated EMSs. The developed method has been successfully integrated in a real robotic picking and packing system and validated with 7 tests of increasing complexity. In these tests, we demonstrate the flexibility of the presented system in handling a wide range of objects in a real dynamic packaging environment. To our knowledge, this is the first time that a complete online picking and packing system is deployed in a real robotic scenario allowing to create mosaics with arbitrary objects and to consider the dynamics of a real robotic packing system.This article has been funded by the European Union's Horizon 2020 research and Innovation Programme under grant agreement No. 780488, and the project "5R-Red Cervera de Tecnologias roboticas en fabricacion inteligente", contract number CER-20211007, under "Centros Tecnologicos de Excelencia Cervera" programme funded by "The Centre for the Development of Industrial Technology (CDTI)"

A Generic ROS-Based Control Architecture for Pest Inspection and Treatment in Greenhouses Using a Mobile Manipulator

To meet the demands of a rising population greenhouses must face the challenge of producing more in a more efficient and sustainable way. Innovative mobile robotic solutions with flexible navigation and manipulation strategies can help monitor the field in real-time. Guided by Integrated Pest Management strategies, robots can perform early pest detection and selective treatment tasks autonomously. However, combining the different robotic skills is an error prone work that requires experience in many robotic fields, usually deriving on ad-hoc solutions that are not reusable in other contexts. This work presents Robotframework, a generic ROS-based architecture which can easily integrate different navigation, manipulation, perception, and high-decision modules leading to a faster and simplified development of new robotic applications. The architecture includes generic real-time data collection tools, diagnosis and error handling modules, and user-friendly interfaces. To demonstrate the benefits of combining and easily integrating different robotic skills using the architecture, two flexible manipulation strategies have been developed to enhance the pest detection in its early state and to perform targeted spraying in simulated and field commercial greenhouses. Besides, an additional use-case has been included to demonstrate the applicability of the architecture in other industrial contexts.This work was supported in part by the GreenPatrol European Project through the European GNSS Agency by the European Union's (EU) Horizon 2020 Research and Innovation Program under Grant 776324 [11]. Documen

Wearable Technology in Automotive Industry: from Training to Real Production

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REVISITING THE END USER'S PERSPECTIVE IN COLLABORATIVE HUMAN-ROBOT INTERACTION

The disciplines of Human-Computer Interaction (HCI) and Human-Robot Interaction (HRI) have evolved rather independently since their early days, mainly because early computers and early robots shared little common ground. However, as computers have jumped off the desktop to pervade the physical world, and as robots extend themselves from the physical world into the cloud, traditional boundaries between these two technological entities have blurred out due to the increasing complexity of their natural habitats. In this paper, we take a snapshot of these converging evolutions, and enquire about the benefits that the human user in HRI can derive from applying HCI methods for R&D, including viewing the collaborative robot itself as an interface

Thermal Tracking in Mobile Robots for Leak Inspection Activities

Maintenance tasks are crucial for all kind of industries, especially in extensive industrial plants, like solar thermal power plants. The incorporation of robots is a key issue for automating inspection activities, as it will allow a constant and regular control over the whole plant. This paper presents an autonomous robotic system to perform pipeline inspection for early detection and prevention of leakages in thermal power plants, based on the work developed within the MAINBOT (http://www.mainbot.eu) European project. Based on the information provided by a thermographic camera, the system is able to detect leakages in the collectors and pipelines. Beside the leakage detection algorithms, the system includes a particle filter-based tracking algorithm to keep the target in the field of view of the camera and to avoid the irregularities of the terrain while the robot patrols the plant. The information provided by the particle filter is further used to command a robot arm, which handles the camera and ensures that the target is always within the image. The obtained results show the suitability of the proposed approach, adding a tracking algorithm to improve the performance of the leakage detection system