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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Andrzej M.J. Skulimowski Wojciech Szulc Decision Science Laboratory AGH University Kraków Poland International Center for Decision Sciences and Forecasting Progress & Business Foundation Kraków Poland Automatic Control and Robotics AGH University

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This article studies the deployment of autonomous robots in smart environments equipped with Industrial Internet of Things (IIoT) infrastructure. First, we characterize state-of-the-art IIoT solutions based on a bibliographic and openweb surveys, focusing on the interaction between autonomous robots and the IIoT infrastructures in the context of Robot-as-a-Service (RaaS) paradigm. Then, we define the criteria and requirements for optimal integration of a robot team equipped with an Internet of Vehicles (IoV) communication protocol with an existing IIoT. Sensors, edge devices, and data exchange algorithms are highlighted as crucial elements of seamless soft- and hardware integration. Establishing a quick interaction of robot decision-making algorithms with IIoT is seen as instrumental in identifying bottlenecks and vulnerabilities of the overall system, and a key to its desired performance. Another relevant issue is safety assurance of robot team in an IIoT environment as reflected in the appropriate standards that advocate responsible and sustainable technological progress in AI-enabled robotic systems. Finally, we will provide a real-life application example illustrating the principles and advantages of appropriate multirobot team integration in covered crops smart horticulture. This example pertains to the relevant area of Agricultural IoT (AIoT) applications, specifically focusing on the design of autonomous fruit-picking robots embedded in a greenhouse or polytunnel control infrastructures. Existing AIoT and crop control is integrated with robot software such as anticipatory coordination algorithms, world model building, navigation, and SLAM. Optimal integration is reached via a prior simulation with a dedicated Digital Twin application implemented in Matlab.

关键词： Performance evaluation Protocols Service robots Robot kinematics Mathematical models Safety Robots Standards Industrial Internet of Things Autonomous robots

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EEG-GNet: GCN-Based EEG Signal Fatigue Detection Network for Edge Devices

EEG-GNet: GCN-Based EEG Signal Fatigue Detection Network for...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Fuquan Wu, Yu Xu, Xinxin Wang, Chuansheng Ma, Minjia Grau, Antoni Huang, Jiayan School of Computer and Big Data Minjiang University Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China College of New Engineering Industry Putian University Putian China Department of Automatic Control Polytechnic University of Catalonia Barcelona Spain School of Robotics Xi'an Jiaotong-Liverpool University Suzhou China College of New Engineering Industry Putian University Fujian Ruituo Information Technology Limited Company Putian China

ISBN: (纸本)9798350386226

Fatigue driving is a common potential traffic safety hazard. To detect and analysis the driver Fatigue degree in real-time, more attention have been increasing paid to application research of EEG fatigue detection device. However, existing methods suffer from complex model structure or large-scale model parameters. In the other words, they requires high computational consumption and large memory footprint, which creates a contradiction between model and portable EEG machine with limited hardware resources. In this work, we take both time and frequency domains of EEG signal into account and design an lightweight and efficient driver fatigue detection network based on GCN (EEG-GNet), which is available edge-end device application. Experiments on 4th Raspberry Pi on a public baseline dataset show that our EEG-GNet outperforms the state-of-the-art methods and takes good tradeoff between detection accuracy and resource consumption. Our EEG-GNet provides a new potential opportunity for future applications in practical portable/wearable (P/W) devices. © 2024 IEEE.

关键词： Electrocardiography

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

Delayless Controllers for Exact Model Matching and Disturban...

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International Conference on Modern Circuits and Systems Technologies (MOCAST)

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

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.

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Investigating the Power Budget of a 3U Nanosatellite Designed for Earth Observation 10

Investigating the Power Budget of a 3U Nanosatellite Designe...

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10th IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2023

作者： Daghouri, Amina El Hachimi, Youssef Ouhammam, Abdelaali Chanoui, Mohammed Alae Elhani, Soumia Mahmoudi, Hassane ENSAM University Center for Research in Space Technologies Energy Optimization Diagnosis and Control Team EMI Mohammed v University Rabat Morocco Power Electronics Smart Control Techniques Automatic and Robotics Team EMI University Center for Research in Space Technologies EMI Mohammed v University Rabat Morocco EST University Center for Research in Space Technologies LASTIMI Laboratory EMI Mohammed v University Rabat Morocco

ISBN: (纸本)9781665456906

The Electrical Power System (EPS) is one of the most critical subsystems of a nanosatellite. Thus, its design should be done carefully for a successful mission. To verify that the power needs of its subsystems does not exceed the power available, a power budget should be established. The purpose of this work is to evaluate the 3U nanosatellite's EPS by analyzing its power budget using Systems Tool Kit (STK) software. In this study, the orbital design, the sizing of the PV panels and the batteries used are presented. The simulation is done taking into account the worst case assumptions: the sun-synchronous Low Earth Orbit (LEO) orbit with the longest eclipse period, the worst case solar irradiance of 1316 W/m2. The results of the power budget established confirm the selection and the sizing of PV panels and the batteries. © 2023 IEEE.

关键词： Electric power utilization

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Implementation of a perception system for autonomous vehicles using a detection-segmentation network in SoC FPGA

arXiv

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arXiv 2023年

作者： Baczmanski, MacIej Wasala, Mateusz Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics Agh University of Krakow Al. Mickiewicza 30 Krakow30-059 Poland

Perception and control systems for autonomous vehicles are an active area of scientific and industrial research. These solutions should be characterised by both high efficiency in recognising obstacles and other environmental elements in different road conditions, real-time capability, and energy efficiency. Achieving such functionality requires an appropriate algorithm and a suitable computing platform. In this paper, we have used the MultiTaskV3 detection-segmentation network as the basis for a perception system that can perform both functionalities within a single architecture. It was appropriately trained, quantised, and implemented on the AMD Xilinx Kria KV260 Vision AI embedded platform. By using this device, it was possible to parallelise and accelerate the computations. Furthermore, the whole system consumes relatively little power compared to a CPU-based implementation (an average of 5 watts, compared to the minimum of 55 watts for weaker CPUs, and the small size (119mm x 140mm x 36mm) of the platform allows it to be used in devices where the amount of space available is limited. It also achieves an accuracy higher than 97% of mAP (mean average precision) for object detection and above 90% of mIoU (mean intersection over union) score for image segmentation. The article also details the design of the Mecanum wheel vehicle, which was used to test the proposed solution in a mock-up city. © 2023, CC BY.

关键词： Field programmable gate arrays (FPGA)

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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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Panhellenic Conference on Electronics and Telecommunications (PACET)

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

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.

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Continuous-Time Ultra-Wideband-Inertial Fusion

arXiv

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arXiv 2023年

作者： Li, Kailai Cao, Ziyu Hanebeck, Uwe D. The Division of Automatic Control Department of Electrical Engineering Linköping University Sweden The Intelligent Sensor-Actuator-Systems Laboratory Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Germany

We introduce a novel framework of continuous-time ultra-wideband-inertial sensor fusion for online motion estimation. Quaternion-based cubic cumulative B-splines are exploited for parameterizing motion states continuously over time. Systematic derivations of analytic kinematic interpolations and spatial differentiations are further provided. Based thereon, a new sliding-window spline fitting scheme is established for asynchronous multi-sensor fusion and online calibration. We conduct a dedicated validation of the quaternion spline fitting method, and evaluate the proposed system, SFUISE (spline fusion-based ultra-wideband-inertial state estimation), in real-world scenarios using public data set and experiments. The proposed sensor fusion system is real-time capable and delivers superior performance over state-of-the-art discrete-time schemes. We release the source code and own experimental data at https://***/KIT-ISAS/SFUISE . Copyright © 2023, The Authors. All rights reserved.

关键词： Motion estimation

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LiDAR-based drone navigation with reinforcement learning

TechRxiv

引用

TechRxiv 2023年

作者： Miera, Pawel Szolc, Hubert Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland

Reinforcement learning is of increasing importance in the field of robot control and simulation plays a key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number of published scientific papers involving this approach. In this work, an autonomous drone control system was prepared to fly forward (according to its coordinates system) and pass the trees encountered in the forest based on the data from a rotating LiDAR sensor. The Proximal Policy Optimization (PPO) algorithm, an example of reinforcement learning (RL), was used to prepare it. A custom simulator in the Python language was developed for this purpose. The Gazebo environment, integrated with the Robot Operating System (ROS), was also used to test the resulting control algorithm. Finally, the prepared solution was implemented in the Nvidia Jetson Nano eGPU and verified in the real tests scenarios. During them, the drone successfully completed the set task and was able to repeatably avoid trees and fly through the forest. © 2023, CC BY.

关键词： Drones

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LiDAR-based drone navigation with reinforcement learning

arXiv

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arXiv 2023年

关键词： Robot Operating System

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MUP-LIO: Mapping Uncertainty-aware Point-wise Lidar Inertial Odometry

MUP-LIO: Mapping Uncertainty-aware Point-wise Lidar Inertial...

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

作者： Hekai Yao Xuetao Zhang Gang Sun Yisha Liu Xuebo Zhang Yan Zhuang Intelligent Robotic Laboratory School of Artificial Intelligence School of Control Science and Engineering Dalian University of Technology Dalian China School of Information Science and Technology Dalian Maritime University Dalian China College of Artificial Intelligence The Institute of Robotics and Automatic Information System (IRAIS) Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper proposes a mapping uncertainty-aware point-wise Lidar Inertial Odometry (LIO), which synthesizes the point-wise point-to-plane match and map refreshment into a probabilistic model. As a result, it can address the issue of mismatching during point registration and remove in-frame motion distortion of Lidar sensors. Specifically, the uncertainty-aware map is designed to embody the uncertainty of map geometric features (points and planes), which comes from the Lidar point measurement and pose estimation. Then the map can be modeled in a probabilistic form. In addition, the proposed framework refreshes map at each Lidar point measurement to timely revise geometric features and provide non-delayed map. On the basis, the probabilistic point-to-plane match method is designed to seek a corresponding plane for each Lidar point in point registration, which can enhance the effectiveness of match and provide adaptive observation noises for more accurate state estimation. Comparative experiments on various public datasets are conducted to demonstrate the superior performance of the proposed framework in terms of higher accuracy and better robustness.

关键词： Laser radar Accuracy Uncertainty Probabilistic logic Distortion Robustness Sensors Odometry Distortion measurement State estimation

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