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135 results on '"Rubagotti, Matteo"'

2. Perceived Safety in Physical Human Robot Interaction -- A Survey

Author

Rubagotti, Matteo, Tusseyeva, Inara, Baltabayeva, Sara, Summers, Danna, and Sandygulova, Anara

Subjects
Computer Science - Robotics
Abstract

This review paper focuses on different aspects of perceived safety for a number of autonomous physical systems. This is a major aspect of robotics research, as more and more applications allow human and autonomous systems to share their space, with crucial implications both on safety and on its perception. The alternative terms used to express related concepts (e.g., psychological safety, trust, comfort, stress, fear, and anxiety) are listed and explained. Then, the available methods to assess perceived safety (i.e., questionnaires, physiological measurements, behavioral assessment, and direct input devices) are described. Six categories of autonomous systems are considered (industrial manipulators, mobile robots, mobile manipulators, humanoid robots, drones, and autonomous vehicles), providing an overview of the main themes related to perceived safety in the specific domain, a description of selected works, and an analysis of how motion and characteristics of the system influence the perception of safety. The survey also discusses experimental duration and location of the reviewed papers as well as identified trends over time., Comment: 23 pages, 3 figures, 4 tables, submitted for journal publication

Published
2021

3. End-to-End Deep Fault Tolerant Control

Author

Baimukashev, Daulet, Rakhim, Bexultan, Rubagotti, Matteo, and Varol, Huseyin Atakan

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Robotics
Abstract

PUBLISHED ON IEEE/ASME TRANSACTIONS ON MECHATRONICS, DOI: 10.1109/TMECH.2021.3100150. Ideally, accurate sensor measurements are needed to achieve a good performance in the closed-loop control of mechatronic systems. As a consequence, sensor faults will prevent the system from working correctly, unless a fault-tolerant control (FTC) architecture is adopted. As model-based FTC algorithms for nonlinear systems are often challenging to design, this paper focuses on a new method for FTC in the presence of sensor faults, based on deep learning. The considered approach replaces the phases of fault detection and isolation and controller design with a single recurrent neural network, which has the value of past sensor measurements in a given time window as input, and the current values of the control variables as output. This end-to-end deep FTC method is applied to a mechatronic system composed of a spherical inverted pendulum, whose configuration is changed via reaction wheels, in turn actuated by electric motors. The simulation and experimental results show that the proposed method can handle abrupt faults occurring in link position/velocity sensors. The provided supplementary material includes a video of real-world experiments and the software source code., Comment: 11 pages, 7 figures

Published
2021
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6. Deep reinforcement learning for PMSG wind turbine control via twin delayed deep deterministic policy gradient (TD3).

Author

Zholtayev, Darkhan, Rubagotti, Matteo, and Do, Ton Duc

Subjects
DEEP reinforcement learning, WIND energy conversion systems, REINFORCEMENT learning, PERMANENT magnet generators, WIND turbines, CONJOINED twins
Abstract

This article proposes the use of a deep reinforcement learning method—and precisely a variant of the deep deterministic policy gradient (DDPG) method known as twin delayed DDPG, or TD3—for maximum power point tracking in wind energy conversion systems that use permanent magnet synchronous generators (PMSGs). An overview of the TD3 algorithm is provided, together with a detailed description of its implementation and training for the considered application. Simulation results are provided, also including a comparison with a model‐based control method based on feedback linearization and linear‐quadratic regulation. The proposed TD3‐based controller achieves a satisfactory control performance and is more robust to PMSG parameter variations as compared to the presented model‐based method. To the best of the authors' knowledge, this article presents for the first time an approach for generating both speed and current control loops using DRL for wind energy conversion systems. [ABSTRACT FROM AUTHOR]

Published
2024
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25. A sub-optimal second order sliding mode controller for systems with saturating actuators

Author

Ferrara, Antonella and Rubagotti, Matteo

Subjects
Algorithm, Algorithms -- Usage, Control systems -- Design and construction, Actuators -- Design and construction
Abstract

In this technical note, the problem of the possible saturation of the continuous control variable in the sub-optimal second order sliding mode controller, applied to systems with saturating actuators, is addressed. It is proved that during the sliding phase, if basic assumptions are made, the continuous control variable never saturates. On the contrary, during the reaching phase, the presence of saturating actuators can make the steering of the sliding variable to zero in a finite time not always guaranteed. In the present technical note, the original algorithm is modified in order to solve this problem: a new strategy is proposed, which proves to be able to steer the sliding variable to zero in a finite time in spite of the presence of saturating actuators. Index Terms--Saturation, sliding mode control, uncertain systems.

Published
2009

48. Platooning control of autonomous nonholonomic mobile robots in a human-robot coexisting environment

Author

Della Vedova, Marco Luigi, Rubagotti, Matteo, Facchinetti, Tullio, Ferrara, Antonella, Della Vedova, Marco Luigi (ORCID:0000-0002-4703-7500), Della Vedova, Marco Luigi, Rubagotti, Matteo, Facchinetti, Tullio, Ferrara, Antonella, and Della Vedova, Marco Luigi (ORCID:0000-0002-4703-7500)

Abstract

This paper proposes a gradient tracking algorithm based on artificial harmonic potential fields, to support the platooning of a team of nonholonomic mobile robots. The main motivation is the need of dynamically changing the goal-point associated with each mobile robot, in order to guarantee the platoon string stability. Mobile obstacles are taken into account with an approach based on the so-called collision cone, and a time-varying artificial security radius is associated with each obstacle, in order to prevent collisions. In addition, the proposed method ensures recovering of the connectivity between robots forming the platoon, after that one of them goes far away from the others and loses the connection during an obstacle avoidance maneuver. Finally, the so-called interference index has been evaluated, to show the low impact of robot motion on human behaviors.

Published
2012

49. Time-optimal sliding-mode control of a mobile robot in a dynamic environment

Author

Rubagotti, Matteo, Della Vedova, Marco Luigi, Ferrara, Antonella, Della Vedova, Marco Luigi (ORCID:0000-0002-4703-7500), Rubagotti, Matteo, Della Vedova, Marco Luigi, Ferrara, Antonella, and Della Vedova, Marco Luigi (ORCID:0000-0002-4703-7500)

Abstract

In this study, an original strategy to control a mobile robot in a dynamic environment is presented. The strategy consists of two main elements. The first is the method for the online trajectory generation based on harmonic potential fields, capable of generating velocity and orientation references, which extends classical results on harmonic potential fields for the case of static environments to the case when the presence of a moving obstacle with unknown motion is considered. The second is the design of sliding-mode controllers capable of making the controlled variables of the robot track in a finite minimum time both the velocity and the orientation references. © 2011 The Institution of Engineering and Technology.

Published
2011

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