Nuno Mendes

Francesca Marafini, Giacomo Zini, Alberto Barontini et al.

The availability of a dataset for validation and verification purposes of novel data-driven strategies and/or hybrid physics-data approaches is currently one of the most pressing challenges in the engineering field. Data ownership, security, access and metadata handiness are currently hindering advances across many fields, particularly in Structural Health Monitoring (SHM) applications. This paper presents a simulated SHM dataset, comprised of dynamic and static measurements (i.e., acceleration and displacement), and includes the conceptual framework designed to generate it. The simulated measurements were generated to incorporate the effects of Environmental and Operational Variations (EOVs), different types of damage, measurement noise and sensor faults and malfunctions, in order to account for scenarios that may occur during real acquisitions. A fixed-fixed steel beam structure was chosen as reference for the numerical benchmark. The simulated monitoring was operated under the assumptions of a Single Degree of Freedom (SDOF) for generating acceleration records and of the Euler-Bernoulli beam for the simulated displacement measurements. The generation process involved the use of parallel computation, which is detailed within the provided open-source code. The generated data is also available open-source, thus ensuring reproducibility, repeatability and accessibility for further research. The comprehensive description of data types, formats, and collection methodologies makes this dataset a valuable resource for researchers aiming to develop or refine SHM techniques, fostering advancements in the field through accessible, high-quality synthetic data.

Pedro Neto, Nuno Mendes, Ricardo Araújo et al.

Purpose - The purpose of this paper is to present a CAD-based human-robot interface that allows non-expert users to teach a robot in a manner similar to that used by human beings to teach each other. Design/methodology/approach - Intuitive robot programming is achieved by using CAD drawings to generate robot programs off-line. Sensory feedback allows minimization of the effects of uncertainty, providing information to adjust the robot paths during robot operation. Findings - It was found that it is possible to generate a robot program from a common CAD drawing and run it without any major concerns about calibration or CAD model accuracy. Research limitations/implications - A limitation of the proposed system has to do with the fact that it was designed to be used for particular technological applications. Practical implications - Since most manufacturing companies have CAD packages in their facilities today, CAD-based robot programming may be a good option to program robots without the need for skilled robot programmers. Originality/value - The paper proposes a new CAD-based robot programming system. Robot programs are directly generated from a CAD drawing running on a commonly available 3D CAD package (Autodesk Inventor) and not from a commercial, computer aided robotics (CAR) software, making it a simple CAD integrated solution. This is a low-cost and low-setup time system where no advanced robot programming skills are required to operate it. In summary, robot programs are generated with a high-level of abstraction from the robot language.

Nuno Mendes, Pedro Neto, Norberto Pires et al.

This paper presents methodologies to discretize nominal robot paths extracted from 3-D CAD drawings. Behind robot path discretization is the ability to have a robot adjusting the traversed paths so that the contact between robot tool and work-piece is properly maintained. In addition, a hybrid force/motion control system based on Fuzzy-PI control is proposed to adjust robot paths with external sensory feedback. All these capabilities allow to facilitate the robot programming process and to increase the robots autonomy.

Pedro Neto, Nuno Mendes, Norberto Pires et al.

More and more, new ways of interaction between humans and robots are desired, something that allow us to program a robot in an intuitive way, quickly and with a high-level of abstraction from the robot language. In this paper is presented a CAD-based system that allows users with basic skills in CAD and without skills in robot programming to generate robot programs from a CAD model of a robotic cell. When the CAD model reproduces exactly the real scenario, the system presents a satisfactory performance. On the contrary, when the CAD model does not reproduce exactly the real scenario or the calibration process is poorly done, we are dealing with uncertain (unstructured environment). In order to minimize or eliminate the previously mentioned problems, it was introduced sensory feedback (force and torque sensing) in the robotic framework. By controlling the end-effector pose and specifying its relationship to the interaction/contact forces, robot programmers can ensure that the robot maneuvers in an unstructured environment, damping possible impacts and also increasing the tolerance to positioning errors from the calibration process. Fuzzy-PI reasoning was used as a force control technique. The effectiveness of the proposed approach was evaluated in a series of experiments.

Pedro Neto, Nuno Mendes

This paper focuses on intuitive and direct off-line robot programming from a CAD drawing running on a common 3-D CAD package. It explores the most suitable way to represent robot motion in a CAD drawing, how to automatically extract such motion data from the drawing, make the mapping of data from the virtual (CAD model) to the real environment and the process of automatic generation of robot paths/programs. In summary, this study aims to present a novel CAD-based robot programming system accessible to anyone with basic knowledge of CAD and robotics. Experiments on different manipulation tasks show the effectiveness and versatility of the proposed approach.

Nuno Mendes, Pedro Neto, J. Norberto Pires et al.

This paper presents a method for robot self-recognition and self-adaptation through the analysis of the contact between the robot end effector and its surrounding environment. Often, in off-line robot programming, the idealized robotic environment (the virtual one) does not reflect accurately the real one. In this situation, we are in the presence of a partially unknown environment (PUE). Thus, robotic systems must have some degree of autonomy to overcome this situation, especially when contact exists. The proposed force/motion control system has an external control loop based on forces and torques exerted on the robot end effector and an internal control loop based on robot motion. The external control loop is tested with an optimal proportional integrative (PI) and a fuzzy-PI controller. The system performance is validated with real-world experiments involving contact in PUEs.