Browsing by Author "Ibarguren, Aitor"
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Item Coordination of Two Robots for Manipulating Heavy and Large Payloads Collaboratively: SOFOCLES Project Case Use(Springer Science and Business Media Deutschland GmbH, 2022-05-26) Bengoa, Pablo; González-Ojeda, Itzel de Jesus; Ibarguren, Aitor; Goenaga, Borja; Martínez-De-Lahidalga, Sandra; Gkournelos, Christos; Lotsaris, Konstantinos; Angelakis, Panagiotis; Makris, Sotiris; Antolín-Urbaneja, Juan Carlos; Garcia, Marcelo V.; Fernández-Peña, Félix; Gordón-Gallegos, Carlos; ROBOTICA_AUTOMA; Tecnalia Research & InnovationDuring the last two decades a great impulse in the development of applications to improve the collaboration between human and robots has been achieved in several sectors. This paper presents a new research carried out for coordinating two robots with the aim to manipulate heavy and large payloads up to 250 kg. This process is performed with the collaboration of the final user who clamps each robot to one point of the part by means of a flexible and reconfigurable tool. The architecture of the system and the followed methodology is envisaged. Also, information about the generation of the trajectory is explained. The work is focused on the coordination problem of two collaboratives robots used in a pick and place application, synchronized with a second process (e.g., sealing, painting, welding). The test has been performed using an 80 kg payload, handling the part synchronously using both collaborative robots, showing good articular coordinates tracking. This research has been done within SOFOCLES project, funded by the European Institute of Innovation and Technology (EIT), a body of the European Union.Item Dual Arm Co-Manipulation Architecture with Enhanced Human–Robot Communication for Large Part Manipulation(Multidisciplinary Digital Publishing Institute (MDPI), 2020-10-29) Ibarguren, Aitor; Eimontaite, Iveta; Outón, José Luis; Fletcher, SarahThe emergence of collaborative robotics has had a great impact on the development of robotic solutions for cooperative tasks nowadays carried out by humans, especially in industrial environments where robots can act as assistants to operators. Even so, the coordinated manipulation of large parts between robots and humans gives rise to many technical challenges, ranging from the coordination of both robotic arms to the human–robot information exchange. This paper presents a novel architecture for the execution of trajectory driven collaborative tasks, combining impedance control and trajectory coordination in the control loop, as well as adding mechanisms to provide effective robot-to-human feedback for a successful and satisfactory task completion. The obtained results demonstrate the validity of the proposed architecture as well as its suitability for the implementation of collaborative robotic systems.Item Path Driven Dual Arm Mobile Co-Manipulation Architecture for Large Part Manipulation in Industrial Environments(2021-10-05) Ibarguren, Aitor; Daelman, Paul; Tecnalia Research & Innovation; ROBOTICA_AUTOMACollaborative part transportation is an interesting application as many industrial sectors require moving large parts among different areas of the workshops, using a large amount of the workforce on this tasks. Even so, the implementation of such kinds of robotic solutions raises technical challenges like force-based control or robot-to-human feedback. This paper presents a path-driven mobile co-manipulation architecture, proposing an algorithm that deals with all the steps of collaborative part transportation. Starting from the generation of force-based twist commands, continuing with the path management for the definition of safe and collaborative areas, and finishing with the feedback provided to the system users, the proposed approach allows creating collaborative lanes for the conveyance of large components. The implemented solution and performed tests show the suitability of the proposed architecture, allowing the creation of a functional robotic system able to assist operators transporting large parts on workshops.Item A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context(2021-05-27) Outón, Jose Luis; Merino, Ibon; Villaverde, Iván; Ibarguren, Aitor; Herrero, Héctor; Daelman, Paul; Sierra, Basilio; Tecnalia Research & Innovation; ROBOTICA_FLEX; ROBOTICA_AUTOMAIn modern industry there are still a large number of low added-value processes that can be automated or semi-automated with safe cooperation between robot and human operators. The European SHERLOCK project aims to integrate an autonomous industrial mobile manipulator (AIMM) to perform cooperative tasks between a robot and a human. To be able to do this, AIMMs need to have a variety of advanced cognitive skills like autonomous navigation, smart perception and task management. In this paper, we report the project’s tackle in a paradigmatic industrial application combining accurate autonomous navigation with deep learning-based 3D perception for pose estimation to locate and manipulate different industrial objects in an unstructured environment. The proposed method presents a combination of different technologies fused in an AIMM that achieve the proposed objective with a success rate of 83.33% in tests carried out in a real environment.