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Proceedings of the 10th Machine Intelligence and Digital Interaction Conference, MIDI 2022

作者： Możaryn, Jakub Department of Mechatronics Institute of Automatic Control and Robotics Warsaw Univeristy of Technology ul. Sw. A. Boboli 8 Warsaw02-525 Poland

ISBN: (纸本)9783031376481

The electronic skin described in the article comprises screen-printed graphene-based sensors, intended to be used for robotic applications. The precise mathematical model allowing the touch pressure estimation is required during its calibration. The article describes the recurrent neural network model for graphene-based electronic skin calibration, in which parameters are not homogeneous, and the touch force characteristics have visible hysteretic behaviour. The presented method provides a simple alternative to the models known in the literature. © 2023, The Author(s).

关键词： Recurrent neural networks

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Versatile Robotic Workstation for Electronic Skin - Problems and Solutions 10th

Versatile Robotic Workstation for Electronic Skin - Problem...

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Proceedings of the 10th Machine Intelligence and Digital Interaction Conference, MIDI 2022

作者： Klimaszewski, Jan Department of Mechatronics Institute of Automatic Control and Robotics Warsaw University of Technology ul. Sw. A. Boboli 8 Warsaw02-525 Poland

ISBN: (纸本)9783031376481

In the face of the Fourth Industrial Revolution (Industry 4.0), collaborative robots have become one of the key pillars of development. Thanks to their sensors, they allow increased flexibility and safety while working in a shared space with humans. One such sensor is the electronic skin (e-skin), which enhances human-robot collaboration through physical contact. This paper presents the developed versatile robotic workstation that allows, among other things, the calibration of e-skin touch measurements. In particular, the problems encountered with the use of a standard industrial robot are presented and ways to solve them are discussed. The presented approach allows the automatic acquisition of calibration measurements of e-skin sensors within the reach of the robot. © 2023, The Author(s).

关键词： Robot Operating System

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Decision Making For Multi-Robot Fixture Planning Using Multi-Agent Reinforcement Learning

TechRxiv

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TechRxiv 2024年

作者： Canzini, Ethan Auledas-Noguera, Marc Pope, Simon Tiwari, Ashutosh Department of Automatic Control & Systems Engineering University of Sheffield United Kingdom Airbus Robotics

Within the realm of flexible manufacturing, fixture layout planning allows manufacturers to rapidly deploy optimal fixturing plans that can reduce surface deformation that leads to crack propagation in components during manufacturing tasks. The role of fixture layout planning has evolved from being performed by experienced engineers to computational methods due to the number of possible configurations for components. Current optimisation methods commonly fall into sub-optimal positions due to the existence of local optima, with data-driven machine learning techniques relying on costly to collect labelled training data. In this paper, we present a framework for multiagent reinforcement learning with team decision theory to find optimal fixturing plans for manufacturing tasks. We demonstrate our approach on two representative aerospace components with complex geometries across a set of drilling tasks, illustrating the capabilities of our method;we will compare this against state of the art methods to showcase our method’s improvement at finding optimal fixturing plans with 3 times the improvement in deformation control within tolerance bounds. © 2024, CC BY.

关键词： Reinforcement learning

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Delayless controllers for Exact Model Matching and Disturbance Rejection of Time Delay Systems with Measurable and Non-measurable Disturbances 12

Delayless Controllers for Exact Model Matching and Disturban...

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12th International Conference on Modern Circuits and Systems Technologies, MOCAST 2023

作者： Koumboulis, Fotis N. Kouvakas, Nikolaos D. National and Kapodistrian University of Athens Euripus Campus Robotics Automatic Control and Cyber-Physical Systems Laboratory Department of Digital Industry Technologies School of Science Euboea Greece

ISBN: (纸本)9798350321074

Delayless control design for time delay systems is an attractive direction for networked control systems as well as other cyber physical applications. In the present paper, the problem of Exact Model Matching with simultaneous Disturbance Rejection (EMMDR) is studied for the case of left-invertible general neutral multi delay systems with measurable and non-measurable disturbances, via two types of delayless controllers. The first type of controllers is a dynamic delayless controller feeding back the measurement outputs, the measurable disturbances and the external commands. The number of the external commands is equal to the number of the control inputs. The second type of controllers is the static delayless version of the first type. For both types of controllers, the necessary and sufficient conditions for the solvability of the problem are established, and the general solutions of the controller matrices are derived. The results are illustrated through a numerical example. © 2023 IEEE.

关键词： controllers

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Tangled Program Graphs as an alternative to DRL-based control algorithms for UAVs 27

Tangled Program Graphs as an alternative to DRL-based contro...

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27th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Szolc, Hubert Desnos, Karol Kryjak, Tomasz AGH University of Krakow Embedded Vision Systems Group Department of Automatic Control and Robotics Kraków Poland Univ Rennes INSA Rennes CNRS IETR - UMR 6164 RennesF-35000 France

ISBN: (纸本)9788362065486

Deep reinforcement learning (DRL) is currently the most popular AI-based approach to autonomous vehicle control. An agent, trained for this purpose in simulation, can interact with the real environment with a human-level performance. Despite very good results in terms of selected metrics, this approach has some significant drawbacks: high computational requirements and low explainability. Because of that, a DRL-based agent cannot be used in some control tasks, especially when safety is the key issue. Therefore we propose to use Tangled Program Graphs (TPGs) as an alternative for deep reinforcement learning in control-related tasks. In this approach, input signals are processed by simple programs that are combined in a graph structure. As a result, TPGs are less computationally demanding and their actions can be explained based on the graph structure. In this paper, we present our studies on the use of TPGs as an alternative for DRL in control-related tasks. In particular, we consider the problem of navigating an unmanned aerial vehicle (UAV) through the unknown environment based solely on the onboard LiDAR sensor. The results of our work show promising prospects for the use of TPGs in control related-tasks. © 2024 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Deep reinforcement learning

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Diagnosing faults in electric motors using B-splines and Bayesian Mixture Model

Diagnosing faults in electric motors using B-splines and Bay...

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International Conference on Methods and Models in Automation and robotics (MMAR)

作者： Kacper Jarzyna Bartłomiej Gawęda Jerzy Baranowski Department of Automatic Control & Robotics AGH University of Science & Technology Kraków Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

Diagnosing faults in electric motors is crucial for various applications, from everyday devices to industrial machinery. Authors propose a method for identifying motor faults using acoustic signals, which are easy to capture with microphones. Proposed approach involves analyzing these signals using Functional Data Analysis (FDA), representing frequency patterns with B-splines and Bayesian Mixture Model as classifier. In this paper, there was developed a classifier to categorize five motor fault types based on these transformed signals. By focusing on frequencies up to 2500 Hz relevant to motor issues, authors aim to detect faults without needing complex equipment and greatly shorten computation time. This approach yields promising results.

关键词： Fault diagnosis Time-frequency analysis Electric potential Focusing Mixture models Bayes methods Splines (mathematics)

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Event-Based Supervisors for the Maintenance Process of a Printing Machine

Event-Based Supervisors for the Maintenance Process of a Pri...

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2024 Panhellenic Conference on Electronics and Telecommunications, PACET 2024

作者： Kouvakas, Nikolaos D. Koumboulis, Fotis N. Fragkoulis, Dimitrios G. Rempelos, Stelios National and Kapodistrian University of Athens Robotics Automatic Control and Cyber-Physical Systems Laboratory Department of Digital Industry Technologies School of Science Euboea 34400 Greece National and Kapodistrian University of Athens Core Department Euboea 34400 Greece

ISBN: (纸本)9798350318845

A set of event-based supervisors is developed to control the maintenance process of a printing machine. The Discrete Event System descriptions of the distinct tasks of the maintenance process are in the form of Finite State Machines. The desired behavior is expressed as four behavioral rules. The rules are translated to regular languages realized by appropriate supervisor automaton. The supervisor's physical realizability is proved and the blocking avoidance of the controlled printing machine is satisfied. © 2024 IEEE.

关键词： Supervisory personnel

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Visual Tracking Nonlinear Model Predictive control Method for Autonomous Wind Turbine Inspection 21

Visual Tracking Nonlinear Model Predictive Control Method fo...

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21st International Conference on Advanced robotics, ICAR 2023

作者： Amer, Abdelhakim Mehndiratta, Mohit Le Fevre Sejersen, Jonas Pham, Huy Xuan Kayacan, Erdal Department of Electrical and Computer Engineering Aarhus C8000 Denmark Gim Robotics Espoo Finland Automatic Control Group Paderborn University Department of Electrical Engineering and Information Technology Paderborn Germany

ISBN: (纸本)9798350342291

Automated visual inspection of on- and off-shorewind turbines using aerial robots provides several benefits, namely, a safe working environment by circumventing the need for workers to be suspended high above the ground, reduced inspection time, preventive maintenance, and access to hard-to-reach areas. A novel nonlinear model predictive control (NMPC) framework alongside a global wind turbine path planner is proposed to achieve distance-optimal coverage for wind turbine inspection. Unlike traditional MPC formulations, visual tracking NMPC (VT-NMPC) is designed to track an inspection surface, instead of a position and heading trajectory, thereby circumventing the need to provide an accurate predefined trajectory for the drone. An additional capability of the proposed VT-NMPC method is that by incorporating inspection requirements as visual tracking costs to minimize, it naturally achieves the inspection task successfully while respecting the physical constraints of the drone. Multiple simulation runs and real-world tests demonstrate the efficiency and efficacy of the proposed automated inspection framework, which outperforms the traditional MPC designs, by providing full coverage of the target wind turbine blades as well as its robustness to changing wind conditions. The implementation codes11https://***/open-airlab/VTNMPC-Autonomous-Wind-Turbine-Inspection are open-sourced. © 2023 IEEE.

关键词： Inspection

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EMOTION RECOGNITION USING BIOMEDICAL SIGNALS IN A MULTIMODAL EMOTION ANALYSIS SYSTEM FOR SOCIAL ROBOTS 38

EMOTION RECOGNITION USING BIOMEDICAL SIGNALS IN A MULTIMODAL...

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38th Annual European Simulation and Modelling Conference, ESM 2024

作者： Skowroński, Kamil Galuszka, Adam Probierz, Eryka Department of Automatic Control and Robotics Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Silesian University of Technology Gliwice Poland Lukasiewicz Research Network Institute of Innovative Technologies EMAG Katowice Poland

ISBN: (纸本)9789492859334

The main purpose of this paper is to review available datasets and artificial intelligence algorithms for the problem of emotion recognition using biomedical signals and to implement the best-adapted solution to a multimodal emotion analysis system. The review takes into account the practical requirements for using solutions in a multimodal emotion analysis system for social robots - the ease of use of devices for collecting biomedical data and the method of categorizing data according to Paul Ekman’s theory. The latest 6 datasets from recent years were reviewed for the given problem in terms of physiological signals, emotion categorization, number of people and stimuli. To better illustrate the work in the given field, a comparison was made of 5 different solutions containing classic artificial intelligence algorithms and popular neural networks. Ultimately, one dataset was selected on which several of the compared solutions were tested and implemented into a multimodal emotion analysis system. The obtained comparison results indicate that despite a large number of diverse datasets from recent years, there are still few publicly available solutions with very high accuracy, especially in the case of neural networks. The proposed issues and solutions may draw more attention to the improvement of social robot systems responsible for communication and companionship. © 2024 Modelling and Simulation 2024 - 38th Annual European Simulation and Modelling Conference 2024, ESM 2024. All rights reserved.

关键词： Social robots

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Generating Continuous Paths On Learned Constraint Manifolds Using Policy Search

Generating Continuous Paths On Learned Constraint Manifolds ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ethan Canzini Simon Pope Ashutosh Tiwari Department of Automatic Control & Systems Engineering University of Sheffield UK Airbus Robotics Airbus UK

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Many robotic manipulation tasks are constrained due to kinematic limitations placed on the object being manipulated. This increases the complexity of manipulation tasks that operate in high dimensions, leading to increased risk that sampling based planners are unable to find optimal solutions. Whilst trajectory optimisation methods provide guaranteed optimal solutions when implementing constraints, they only provide locally optimal solutions in sequential decision-making and struggle to provide globally optimal paths. These constraints can be incorporated into the probabilistic latent spaces by using demonstrations that satisfy the constraint function. However whenever constraints change or a manipulator must perform different tasks the network must be retrained to accommodate the new constraints. In this paper, we provide an approach that allows the training of a single learned manifold that can be augmented to determine the constraint manifold for the manipulation task. Using this manifold, the geodesic between two points can be computed using policy search to solve the cost function associated with the geodesic curve length ${\mathcal{L}_\gamma }$. We provide comparisons in terms of path length against popular path planning algorithms with different kinematic constraints, demonstrating our method’s ability to find optimal shortest paths on constraint manifolds.

关键词： Manifolds Training Runtime Optimization methods Kinematics Reinforcement learning Probabilistic logic Real-time systems Trajectory Splines (mathematics)

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