There is a paradigm shift in current manufacturing needs that is causing a change from the current mass-production-based approach to a mass customization approach where production volumes are smaller and more variable. Current processes are very adapted to the previous paradigm and lack the required flexibility to adapt to the new production needs. To solve this problem, an innovative industrial mobile manipulator is presented. The robot is equipped with a variety of sensors that allow it to perceive its surroundings and perform complex tasks in dynamic environments. Following the current needs of the industry, the robot is capable of autonomous navigation, safely avoiding obstacles. It is flexible enough to be able to perform a wide variety of tasks, being the change between tasks done easily thanks to skills-based programming and the ability to change tools autonomously. In addition, its security systems allow it to share the workspace with human operators. This prototype has been developed as part of THOMAS European project, and it has been tested and demonstrated in real-world manufacturing use cases.

The 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.

In 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.

This paper presents a state machine-based architecture, which enhances the flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes, increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating the presented approach versus traditional robot programming techniques.

Current operations involving Dismantling and Decommissioning (D&D) in nuclear and other harsh environments rely on manual inspection and assessment of the sites, exposing human operators to potentially dangerous situations. This work presents a reconfigurable Autonomous Mobile Robot (AMR) able to mount a wide range of nuclear sensors for flexible and modular inspection tasks in these operations. This AMR is part of the CLEANDEM solution, which uses Unmanned Ground Vehicles (UGVs), nuclear sensors, and a Digital Twin to facilitate a tool for improving D&D operations in nuclear sites. Both the AMR used as a UGV and the system have been successfully tested in real nuclear sites, showing that these tools can greatly aid in operations management and hazard reduction.

In a context of a pandemic caused by the SARS-CoV-2 virus, there is a need to disinfect busy areas such as schools, hospitals, nursing homes, laboratories, public transport, etc. using techniques that pose a risk to health. In turn, the robotics industry is at a critical moment with great developments and applications in numerous applications. Therefore, the figure of robots is of great interest as they have the ability to perform these tasks autonomously. However, there are great challenges in current robotics that must be resolved in order to perform tasks correctly. This is the specific case of door opening. Something necessary since to achieve a complete disinfection the robot must go through all the rooms of the installation. In this work, a solution to the problem of opening doors is presented by means of a mobile robot to which artificial perception techniques are applied for detection, handling and autonomous navigation. Keywords: autonomous navigation, artificial perception, learning by demonstration, skills-based programming, door opening, AIMM, mobile robotics, sensor fusion En un contexto de pandemia provocada por el virus SARS-CoV-2 surge la necesidad de desinfectar zonas transitadas como colegios, hospitales, residencias de mayores, laboratorios, transporte público, etc. mediante técnicas que suponen un riesgo para la salud. A su vez, la industria de la robótica se encuentra en un momento álgido con grandes desarrollos y aplicaciones en numerosos ámbitos. Por ello, la figura de los robots cobra un gran interés al poseer la capacidad de realizar estas tareas de modo autónomo. No obstante, existen grandes retos en la robótica actual que deben ser resueltos para poder desempeñar las tareas correctamente. Es el caso concreto de la apertura de puertas. Algo necesario ya que para lograr una desinfección completa el robot debe atravesar todas las estancias de la instalación. En este trabajo se presenta una solución al problema de la apertura de puertas mediante un robot móvil al que se le aplican técnicas de percepción artificial para detección, manipulación y navegación autónoma. Palabras clave: navegación autónoma, percepción artificial, aprendizaje por demostración, programación basada en habilidades, apertura de puertas, AIMM, robótica móvil, fusión de sensores