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Ludek Zalud

Brno University of Technology, Department of Control and Instrumentation, Faculty Member

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Sultanus Salehin

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Monash

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North Carolina State University

Sapientia University, Cluj-Napoca

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Fuzhou University

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Papers by Ludek Zalud

Image Processing on Raspberry Pi for Mobile Robotics

International Journal of Signal Processing Systems, Dec 1, 2016

We have designed a small robot called Cube for simple robotics tasks and students works. The Cube... more We have designed a small robot called Cube for simple robotics tasks and students works. The Cube carries only small and lightweight computational platform Raspberry Pi equipped with a camera. This paper serves as an introduction to using image processing methods on a Raspberry Pi platform via Simulink in Matlab. We have designed a cheap framework for fast image processing in real-time including feature extraction and image transformation methods. In the paper a several selected methods frequently used not only in robotics are implemented and tested on the Raspberry Pi 2 equipped with a native camera board. Algorithms for edge, corner and line detection have been implemented by using Simulink with the Computer Vision System Toolbox and other in-build tools. 

Atlas Fusion - Modern Framework for Autonomous Agent Sensor Data Fusion

2022 ELEKTRO (ELEKTRO)

In this paper, we present our software sensor fusion framework for self-driving cars and other au... more In this paper, we present our software sensor fusion framework for self-driving cars and other autonomous robots. We have designed our framework as a universal and scalable platform for building up a robust 3D model of the agent's surrounding environment by fusing a wide range of various sensors into the data model that we can use as a basement for the decision making and planning algorithms. Our software currently covers the data fusion of the RGB and thermal cameras, 3D LiDARs, 3D IMU, and a GNSS positioning. The framework covers a complete pipeline from data loading, filtering, preprocessing, environment model construction, visualization, and data storage. The architecture allows the community to modify the existing setup or to extend our solution with new ideas. The entire software is fully compatible with ROS (Robotic Operation System), which allows the framework to cooperate with other ROS-based software. The

Three-dimensional Thermal Imaging in Medicine

Proceedings of 3DBODY.TECH 2017 - 8th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Montreal QC, Canada, 11-12 Oct. 2017, 2017

The digital medical thermal imaging is valuable qualitative tool for detection of inflamed or nec... more The digital medical thermal imaging is valuable qualitative tool for detection of inflamed or necrotic areas, but it lacks the ability of quantification. The new 3D scanning system RoScan composed from robotic manipulator, laser scanner, color camera and thermal imager is presented, extending medical thermal imaging with possibility of quantification, allowing specific ROI selection and bringing higher thermal resolution in resulting outputs. It helps to solve the current problem of medical quantification, which permeates through the many medical sectors. The advantages of RoScan are demonstrated on sample experiment, which shows the benefits of proposed device.

Image Processing on Raspberry Pi in Matlab

This paper serves as an introduction to using image processing methods on a Raspberry Pi platform... more This paper serves as an introduction to using image processing methods on a Raspberry Pi platform via Simulink in Matlab. We have designed a cheap framework for fast image processing in real-time including feature extraction and image transformation methods. In the paper a several selected methods frequently used not only in robotics are implemented and tested on the Raspberry Pi 2 equipped with a native camera board. Algorithms for edge, corner and line detection have been implemented by using Simulink with the Computer Vision System Toolbox and other in-build tools.

Line segment similarity criterion for vector images

Vector representation of the images, maps, schematics and other information is widely used, and i... more Vector representation of the images, maps, schematics and other information is widely used, and in computer processing of these data, comparison and similarity evaluation of two sets of line segments is often necessary. Various techniques are already in use, but these mostly rely on the algorithmic functions such as minimum/maximum of two or more variables, which limits their applicability for many optimization algorithms. In this paper we propose a novel area based criterion function for line segment similarity evaluation, which is easily differentiable and the derivatives are continuous in the whole domain of definition. The second important feature is the possibility of preprocessing of the input data. Once finished, it takes constant time to evaluate the criterion for different transformations of one of the input sets of line segments. This has potential to greatly speed up iterative matching algorithms. In such case, the computational complexity is reduced from O(pt) to O(p+ t)...

Brno urban dataset: Winter extension

Data in Brief, 2021

This paper presents our latest extension of the Brno Urban Dataset (BUD), the Winter Extension (W... more This paper presents our latest extension of the Brno Urban Dataset (BUD), the Winter Extension (WE). The dataset contains data from commonly used sensors in the automotive industry, like four RGB and single IR cameras, three 3D LiDARs, differential RTK GNSS receiver with heading estimation, the IMU and FMCW radar. Data from all sensors are precisely timestamped for future offline interpretation and data fusion. The most significant gain of the dataset is the focus on the winter conditions in snow-covered environments. Only a few public datasets deal with these kinds of conditions. We recorded the dataset during February 2021 in Brno, Czechia, when fresh snow covers the entire city and the surrounding countryside. The dataset contains situations from the city center, suburbs, highways as well as the countryside. Overall, the new extension adds three hours of real-life traffic situations from the mid-size city to the existing 10 h of original records. Additionally, we provide the precalculated YOLO neural network object detection annotations for all five cameras for the entire old data and the new ones. The dataset is suitable for developing mapping and navigation algorithms as well as the collision and object detection pipelines. The entire dataset is available as open-source under the MIT license.

Fully Automated DCNN-Based Thermal Images Annotation Using Neural Network Pretrained on RGB Data

Sensors, 2021

One of the biggest challenges of training deep neural network is the need for massive data annota... more One of the biggest challenges of training deep neural network is the need for massive data annotation. To train the neural network for object detection, millions of annotated training images are required. However, currently, there are no large-scale thermal image datasets that could be used to train the state of the art neural networks, while voluminous RGB image datasets are available. This paper presents a method that allows to create hundreds of thousands of annotated thermal images using the RGB pre-trained object detector. A dataset created in this way can be used to train object detectors with improved performance. The main gain of this work is the novel method for fully automatic thermal image labeling. The proposed system uses the RGB camera, thermal camera, 3D LiDAR, and the pre-trained neural network that detects objects in the RGB domain. Using this setup, it is possible to run the fully automated process that annotates the thermal images and creates the automatically ann...

Brno Urban Dataset - The New Data for Self-Driving Agents and Mapping Tasks

2020 IEEE International Conference on Robotics and Automation (ICRA), 2020

Autonomous driving is a dynamically growing field of research, where quality and amount of experi... more Autonomous driving is a dynamically growing field of research, where quality and amount of experimental data is critical. Although several rich datasets are available these days, the demands of researchers and technical possibilities are evolving. Through this paper, we bring a new dataset recorded in Brno-Czech Republic. It offers data from four WUXGA cameras, two 3D LiDARs, inertial measurement unit, infrared camera and especially differential RTK GNSS receiver with centimetre accuracy which, to the best knowledge of the authors, is not available from any other public dataset so far. In addition, all the data are precisely timestamped with submillisecond precision to allow wider range of applications. At the time of publishing of this paper, recordings of more than 350 km of rides in varying environment are shared at: https: //github.com/RoboticsBUT/Brno-Urban-Dataset.

Visual Diagnosis of the Varroa Destructor Parasitic Mite in Honeybees Using Object Detector Techniques

Sensors, 2021

The Varroa destructor mite is one of the most dangerous Honey Bee (Apis mellifera) parasites worl... more The Varroa destructor mite is one of the most dangerous Honey Bee (Apis mellifera) parasites worldwide and the bee colonies have to be regularly monitored in order to control its spread. In this paper we present an object detector based method for health state monitoring of bee colonies. This method has the potential for online measurement and processing. In our experiment, we compare the YOLO and SSD object detectors along with the Deep SVDD anomaly detector. Based on the custom dataset with 600 ground-truth images of healthy and infected bees in various scenes, the detectors reached the highest F1 score up to 0.874 in the infected bee detection and up to 0.714 in the detection of the Varroa destructor mite itself. The results demonstrate the potential of this approach, which will be later used in the real-time computer vision based honey bee inspection system. To the best of our knowledge, this study is the first one using object detectors for the Varroa destructor mite detection ...

Robotic Template Library

Journal of Open Research Software, 2021

Robotic Template Library (RTL) is a set of tools for dealing with geometry and point cloud proces... more Robotic Template Library (RTL) is a set of tools for dealing with geometry and point cloud processing, especially in robotic applications. The software package covers basic objects such as vectors, line segments, quaternions, rigid transformations, etc., however, its main contribution lies in the more advanced modules: The segmentation module for batch or stream clustering of point clouds, the fast vectorization module for approximation of continuous point clouds by geometric objects of higher grade and the LaTeX export module enabling automated generation of high-quality visual outputs. It is a header-only library written in C++17, uses the Eigen library as a linear algebra back-end, and is designed with high computational performance in mind. RTL can be used in all robotic tasks such as motion planning, map building, object recognition and many others, but the point cloud processing utilities are general enough to be employed in any field touching object reconstruction and computer vision applications as well.

The RoScan Thermal 3D Body Scanning System: Medical Applicability and Benefits for Unobtrusive Sensing and Objective Diagnosis

Sensors, 2020

The RoScan is a novel, high-accuracy multispectral surface scanning system producing colored 3D m... more The RoScan is a novel, high-accuracy multispectral surface scanning system producing colored 3D models that include a thermal layer. (1) Background: at present, medicine still exhibits a lack of objective diagnostic methods. As many diseases involve thermal changes, thermography may appear to be a convenient technique for the given purpose; however, there are three limiting problems: exact localization, resolution vs. range, and impossibility of quantification. (2) Methods: the basic principles and benefits of the system are described. The procedures rely on a robotic manipulator with multiple sensors to create a multispectral 3D model. Importantly, the structure is robust, scene-independent, and features quantifiable measurement uncertainty; thus, all of the above problems of medical thermography are resolved. (3) Results: the benefits were demonstrated by several pilot case studies: medicament efficacy assessment in dermatology, objective recovery progress assessment in traumatolo...

DeskBalance: Novel Gamified System for Diagnosis and Treatment of Postural Stability

IFAC-PapersOnLine, 2016

This paper introduces novel, very cheap and easy-to-use system for postural-stability analysis, p... more This paper introduces novel, very cheap and easy-to-use system for postural-stability analysis, providing both diagnostic and therapeutic functions. It can be used by therapists to quantify patient's postural stability, and also by patients itself for home training, where gamification is used to keep a patient motivated to practice prescribed exercises. The system composes from wobble board (platform with solid spherical bottom side) equipped by smartphone mounted to platform by holder. Tilt of board is measured in two degrees of freedom and transferred to laptop via Bluetooth, in which acquired data are processed and visualized. The system principles and its functions are described. The method is compared with present standard methods. The accuracy of measurements is derived and experimentally verified. Verification experiments proves, that much more expensive commercial solutions can be fully replaced with this cheap solution.

Cooperation between an unmanned aerial vehicle and an unmanned ground vehicle in highly accurate localization of gamma radiation hotspots

International Journal of Advanced Robotic Systems, 2018

This article discusses the highly autonomous robotic search and localization of radiation sources... more This article discusses the highly autonomous robotic search and localization of radiation sources in outdoor environments. The cooperation between a human operator, an unmanned aerial vehicle, and an unmanned ground vehicle is used to render the given mission highly effective, in accordance with the idea that the search for potential radiation sources should be fast, precise, and reliable. Each of the components assumes its own role in the mission; the unmanned aerial vehicle (in our case, a multirotor) is responsible for fast data acquisition to create an accurate orthophoto and terrain map of the zone of interest. Aerial imagery is georeferenced directly, using an onboard sensor system, and no ground markers are required. The unmanned aerial vehicle can also perform rough radiation measurement, if necessary. Since the map contains three-dimensional information about the environment, algorithms to compute the spatial gradient, which represents the rideability, can be designed. Base...

Reconnaissance Micro Uav System

Acta Polytechnica CTU Proceedings, 2015

The Design and Implementation of Quadrotor UAV

Advances in Intelligent Systems and Computing, 2015

Limb volume measurements: comparison of accuracy and decisive parameters of the most used present methods

by Ludek Zalud and Adam Chromy

SpringerPlus, 2015

Limb volume measurements are used for evaluating growth of muscle mass and effectivity of strengt... more Limb volume measurements are used for evaluating growth of muscle mass and effectivity of strength training. Beside sport sciences, it is used e.g. for detection of oedemas, lymphedemas or carcinomas or for examinations of muscle atrophy. There are several commonly used methods, but there is a lack of clear comparison, which shows their advantages and limits. The accuracy of each method is uncertainly estimated only. The aim of this paper is to determine and experimentally verify their accuracy and compare them among each other. Water Displacement Method (WD), three methods based on circumferential measures-Frustum Sign Model (FSM), Disc Model (DM), Partial Frustum Model (PFM) and two 3D scan based methods Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) were compared. Precise reference cylinders and limbs of two human subjects were measured 10 times by each method. Personal dependency of methods was also tested by measuring 10 times the same object by 3 different people. Accuracies: WD 0.3 %, FSM 2-8 % according person, DM, PFM 1-8 %, MRI 2 % (hand) or 8 % (finger), CT 0.5 % (hand) or 2 % (finger);times: FSM 1 min, CT 7 min, WD, DM, PFM 15 min, MRI 19 min; and more. WD was found as the best method for most of uses with best accuracy. The CT disposes with almost the same accuracy and allows measurements of specific regions (e.g. particular muscles), as same as MRI, which accuracy is worse though, but it is not harmful. Frustum Sign Model is usable for very fast estimation of limb volume, but with lower accuracy, Disc Model and Partial Frustum Model is useful in cases when Water Displacement cannot be used.

Effective Calibration and Evaluation of Multi-Camera Robotic Head

International Journal of Advanced Computer Science and Applications, 2015

Breath Analysis Using a Time-of-Flight Camera and Pressure Belts

by Ludek Zalud and Jana Kolarova

Artificial organs, Jan 3, 2015

The proper way of breathing is important for everyone. Healthy people often do not follow respira... more The proper way of breathing is important for everyone. Healthy people often do not follow respiration until breathing problems start-during stress or during sport activity in physiological cases. More serious cases are stroke, injury, or surgery of the chest and others. So, learning to breathe correctly and/or breathing diagnosis is considerable for many reasons. Two novel methods of breath analysis suitable for diagnostics and rehabilitation are presented. The first technique utilizes pressure belts fastened to the patient's belly and chest, and the second method relies on a SwissRanger SR-4000 time-of-flight camera. The measurement principles are described together with the advantages and disadvantages of the applied techniques. The SwissRanger camera depth calibration is proposed to facilitate better results during the breath analysis. The methods are tested on a group of students to provide a comparison of their individual performances. As it was demonstrated, presented meth...

ARGOS - ORPHEUS-X2 User Interface

Orpheus reconnaissance robotic system Orpheus-X2 developed at Department of Control and Instrumen... more Orpheus reconnaissance robotic system Orpheus-X2 developed at Department of Control and Instrumentation is described. The paper is focused to ARGOS visualization software system for sensory supported visual telepresence control of mobile robots. The article describes augmented reality part of the system - namely visual telepresence, 2D and 3D proximity scanner data and inertial sensor data presentation. The concept of real video in background of operator's view with a series of Virtual Head-up Displays is presented. Advantages of ARGOS for real- time data fusion of CCD color camera, thremovision and 3D proximity scanner are depicted.

3D proximity scanner integration to rescue robotic system

Orpheus mobile robot is a teleoperated device primarily designed for remote exploration of hazard... more Orpheus mobile robot is a teleoperated device primarily designed for remote exploration of hazardous places and rescue missions. The robot is able to operate both indoors and outdoors, is made to be durable and reliable. The device is controlled through advanced user interface with joystick and head mounted display with inertial head movement sensor. To increase the system's operability in difficult conditions (fog, smoke, dark), 3D proximity scanner controlled by on-board processor through Ethernet connection was integrated to it. The scanner also represents a step towards semi-autonomous mode of the robot.

Image Processing on Raspberry Pi for Mobile Robotics

International Journal of Signal Processing Systems, Dec 1, 2016

We have designed a small robot called Cube for simple robotics tasks and students works. The Cube... more We have designed a small robot called Cube for simple robotics tasks and students works. The Cube carries only small and lightweight computational platform Raspberry Pi equipped with a camera. This paper serves as an introduction to using image processing methods on a Raspberry Pi platform via Simulink in Matlab. We have designed a cheap framework for fast image processing in real-time including feature extraction and image transformation methods. In the paper a several selected methods frequently used not only in robotics are implemented and tested on the Raspberry Pi 2 equipped with a native camera board. Algorithms for edge, corner and line detection have been implemented by using Simulink with the Computer Vision System Toolbox and other in-build tools. 

Atlas Fusion - Modern Framework for Autonomous Agent Sensor Data Fusion

2022 ELEKTRO (ELEKTRO)

In this paper, we present our software sensor fusion framework for self-driving cars and other au... more In this paper, we present our software sensor fusion framework for self-driving cars and other autonomous robots. We have designed our framework as a universal and scalable platform for building up a robust 3D model of the agent's surrounding environment by fusing a wide range of various sensors into the data model that we can use as a basement for the decision making and planning algorithms. Our software currently covers the data fusion of the RGB and thermal cameras, 3D LiDARs, 3D IMU, and a GNSS positioning. The framework covers a complete pipeline from data loading, filtering, preprocessing, environment model construction, visualization, and data storage. The architecture allows the community to modify the existing setup or to extend our solution with new ideas. The entire software is fully compatible with ROS (Robotic Operation System), which allows the framework to cooperate with other ROS-based software. The

Three-dimensional Thermal Imaging in Medicine

Proceedings of 3DBODY.TECH 2017 - 8th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Montreal QC, Canada, 11-12 Oct. 2017, 2017

The digital medical thermal imaging is valuable qualitative tool for detection of inflamed or nec... more The digital medical thermal imaging is valuable qualitative tool for detection of inflamed or necrotic areas, but it lacks the ability of quantification. The new 3D scanning system RoScan composed from robotic manipulator, laser scanner, color camera and thermal imager is presented, extending medical thermal imaging with possibility of quantification, allowing specific ROI selection and bringing higher thermal resolution in resulting outputs. It helps to solve the current problem of medical quantification, which permeates through the many medical sectors. The advantages of RoScan are demonstrated on sample experiment, which shows the benefits of proposed device.

Image Processing on Raspberry Pi in Matlab

This paper serves as an introduction to using image processing methods on a Raspberry Pi platform... more This paper serves as an introduction to using image processing methods on a Raspberry Pi platform via Simulink in Matlab. We have designed a cheap framework for fast image processing in real-time including feature extraction and image transformation methods. In the paper a several selected methods frequently used not only in robotics are implemented and tested on the Raspberry Pi 2 equipped with a native camera board. Algorithms for edge, corner and line detection have been implemented by using Simulink with the Computer Vision System Toolbox and other in-build tools.

Line segment similarity criterion for vector images

Vector representation of the images, maps, schematics and other information is widely used, and i... more Vector representation of the images, maps, schematics and other information is widely used, and in computer processing of these data, comparison and similarity evaluation of two sets of line segments is often necessary. Various techniques are already in use, but these mostly rely on the algorithmic functions such as minimum/maximum of two or more variables, which limits their applicability for many optimization algorithms. In this paper we propose a novel area based criterion function for line segment similarity evaluation, which is easily differentiable and the derivatives are continuous in the whole domain of definition. The second important feature is the possibility of preprocessing of the input data. Once finished, it takes constant time to evaluate the criterion for different transformations of one of the input sets of line segments. This has potential to greatly speed up iterative matching algorithms. In such case, the computational complexity is reduced from O(pt) to O(p+ t)...

Brno urban dataset: Winter extension

Data in Brief, 2021

This paper presents our latest extension of the Brno Urban Dataset (BUD), the Winter Extension (W... more This paper presents our latest extension of the Brno Urban Dataset (BUD), the Winter Extension (WE). The dataset contains data from commonly used sensors in the automotive industry, like four RGB and single IR cameras, three 3D LiDARs, differential RTK GNSS receiver with heading estimation, the IMU and FMCW radar. Data from all sensors are precisely timestamped for future offline interpretation and data fusion. The most significant gain of the dataset is the focus on the winter conditions in snow-covered environments. Only a few public datasets deal with these kinds of conditions. We recorded the dataset during February 2021 in Brno, Czechia, when fresh snow covers the entire city and the surrounding countryside. The dataset contains situations from the city center, suburbs, highways as well as the countryside. Overall, the new extension adds three hours of real-life traffic situations from the mid-size city to the existing 10 h of original records. Additionally, we provide the precalculated YOLO neural network object detection annotations for all five cameras for the entire old data and the new ones. The dataset is suitable for developing mapping and navigation algorithms as well as the collision and object detection pipelines. The entire dataset is available as open-source under the MIT license.

Fully Automated DCNN-Based Thermal Images Annotation Using Neural Network Pretrained on RGB Data

Sensors, 2021

One of the biggest challenges of training deep neural network is the need for massive data annota... more One of the biggest challenges of training deep neural network is the need for massive data annotation. To train the neural network for object detection, millions of annotated training images are required. However, currently, there are no large-scale thermal image datasets that could be used to train the state of the art neural networks, while voluminous RGB image datasets are available. This paper presents a method that allows to create hundreds of thousands of annotated thermal images using the RGB pre-trained object detector. A dataset created in this way can be used to train object detectors with improved performance. The main gain of this work is the novel method for fully automatic thermal image labeling. The proposed system uses the RGB camera, thermal camera, 3D LiDAR, and the pre-trained neural network that detects objects in the RGB domain. Using this setup, it is possible to run the fully automated process that annotates the thermal images and creates the automatically ann...

Brno Urban Dataset - The New Data for Self-Driving Agents and Mapping Tasks

2020 IEEE International Conference on Robotics and Automation (ICRA), 2020

Autonomous driving is a dynamically growing field of research, where quality and amount of experi... more Autonomous driving is a dynamically growing field of research, where quality and amount of experimental data is critical. Although several rich datasets are available these days, the demands of researchers and technical possibilities are evolving. Through this paper, we bring a new dataset recorded in Brno-Czech Republic. It offers data from four WUXGA cameras, two 3D LiDARs, inertial measurement unit, infrared camera and especially differential RTK GNSS receiver with centimetre accuracy which, to the best knowledge of the authors, is not available from any other public dataset so far. In addition, all the data are precisely timestamped with submillisecond precision to allow wider range of applications. At the time of publishing of this paper, recordings of more than 350 km of rides in varying environment are shared at: https: //github.com/RoboticsBUT/Brno-Urban-Dataset.

Visual Diagnosis of the Varroa Destructor Parasitic Mite in Honeybees Using Object Detector Techniques

Sensors, 2021

The Varroa destructor mite is one of the most dangerous Honey Bee (Apis mellifera) parasites worl... more The Varroa destructor mite is one of the most dangerous Honey Bee (Apis mellifera) parasites worldwide and the bee colonies have to be regularly monitored in order to control its spread. In this paper we present an object detector based method for health state monitoring of bee colonies. This method has the potential for online measurement and processing. In our experiment, we compare the YOLO and SSD object detectors along with the Deep SVDD anomaly detector. Based on the custom dataset with 600 ground-truth images of healthy and infected bees in various scenes, the detectors reached the highest F1 score up to 0.874 in the infected bee detection and up to 0.714 in the detection of the Varroa destructor mite itself. The results demonstrate the potential of this approach, which will be later used in the real-time computer vision based honey bee inspection system. To the best of our knowledge, this study is the first one using object detectors for the Varroa destructor mite detection ...

Robotic Template Library

Journal of Open Research Software, 2021

Robotic Template Library (RTL) is a set of tools for dealing with geometry and point cloud proces... more Robotic Template Library (RTL) is a set of tools for dealing with geometry and point cloud processing, especially in robotic applications. The software package covers basic objects such as vectors, line segments, quaternions, rigid transformations, etc., however, its main contribution lies in the more advanced modules: The segmentation module for batch or stream clustering of point clouds, the fast vectorization module for approximation of continuous point clouds by geometric objects of higher grade and the LaTeX export module enabling automated generation of high-quality visual outputs. It is a header-only library written in C++17, uses the Eigen library as a linear algebra back-end, and is designed with high computational performance in mind. RTL can be used in all robotic tasks such as motion planning, map building, object recognition and many others, but the point cloud processing utilities are general enough to be employed in any field touching object reconstruction and computer vision applications as well.

The RoScan Thermal 3D Body Scanning System: Medical Applicability and Benefits for Unobtrusive Sensing and Objective Diagnosis

Sensors, 2020

The RoScan is a novel, high-accuracy multispectral surface scanning system producing colored 3D m... more The RoScan is a novel, high-accuracy multispectral surface scanning system producing colored 3D models that include a thermal layer. (1) Background: at present, medicine still exhibits a lack of objective diagnostic methods. As many diseases involve thermal changes, thermography may appear to be a convenient technique for the given purpose; however, there are three limiting problems: exact localization, resolution vs. range, and impossibility of quantification. (2) Methods: the basic principles and benefits of the system are described. The procedures rely on a robotic manipulator with multiple sensors to create a multispectral 3D model. Importantly, the structure is robust, scene-independent, and features quantifiable measurement uncertainty; thus, all of the above problems of medical thermography are resolved. (3) Results: the benefits were demonstrated by several pilot case studies: medicament efficacy assessment in dermatology, objective recovery progress assessment in traumatolo...

DeskBalance: Novel Gamified System for Diagnosis and Treatment of Postural Stability

IFAC-PapersOnLine, 2016

This paper introduces novel, very cheap and easy-to-use system for postural-stability analysis, p... more This paper introduces novel, very cheap and easy-to-use system for postural-stability analysis, providing both diagnostic and therapeutic functions. It can be used by therapists to quantify patient's postural stability, and also by patients itself for home training, where gamification is used to keep a patient motivated to practice prescribed exercises. The system composes from wobble board (platform with solid spherical bottom side) equipped by smartphone mounted to platform by holder. Tilt of board is measured in two degrees of freedom and transferred to laptop via Bluetooth, in which acquired data are processed and visualized. The system principles and its functions are described. The method is compared with present standard methods. The accuracy of measurements is derived and experimentally verified. Verification experiments proves, that much more expensive commercial solutions can be fully replaced with this cheap solution.

Cooperation between an unmanned aerial vehicle and an unmanned ground vehicle in highly accurate localization of gamma radiation hotspots

International Journal of Advanced Robotic Systems, 2018

This article discusses the highly autonomous robotic search and localization of radiation sources... more This article discusses the highly autonomous robotic search and localization of radiation sources in outdoor environments. The cooperation between a human operator, an unmanned aerial vehicle, and an unmanned ground vehicle is used to render the given mission highly effective, in accordance with the idea that the search for potential radiation sources should be fast, precise, and reliable. Each of the components assumes its own role in the mission; the unmanned aerial vehicle (in our case, a multirotor) is responsible for fast data acquisition to create an accurate orthophoto and terrain map of the zone of interest. Aerial imagery is georeferenced directly, using an onboard sensor system, and no ground markers are required. The unmanned aerial vehicle can also perform rough radiation measurement, if necessary. Since the map contains three-dimensional information about the environment, algorithms to compute the spatial gradient, which represents the rideability, can be designed. Base...

Reconnaissance Micro Uav System

Acta Polytechnica CTU Proceedings, 2015

The Design and Implementation of Quadrotor UAV

Advances in Intelligent Systems and Computing, 2015

Limb volume measurements: comparison of accuracy and decisive parameters of the most used present methods

by Ludek Zalud and Adam Chromy

SpringerPlus, 2015

Limb volume measurements are used for evaluating growth of muscle mass and effectivity of strengt... more Limb volume measurements are used for evaluating growth of muscle mass and effectivity of strength training. Beside sport sciences, it is used e.g. for detection of oedemas, lymphedemas or carcinomas or for examinations of muscle atrophy. There are several commonly used methods, but there is a lack of clear comparison, which shows their advantages and limits. The accuracy of each method is uncertainly estimated only. The aim of this paper is to determine and experimentally verify their accuracy and compare them among each other. Water Displacement Method (WD), three methods based on circumferential measures-Frustum Sign Model (FSM), Disc Model (DM), Partial Frustum Model (PFM) and two 3D scan based methods Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) were compared. Precise reference cylinders and limbs of two human subjects were measured 10 times by each method. Personal dependency of methods was also tested by measuring 10 times the same object by 3 different people. Accuracies: WD 0.3 %, FSM 2-8 % according person, DM, PFM 1-8 %, MRI 2 % (hand) or 8 % (finger), CT 0.5 % (hand) or 2 % (finger);times: FSM 1 min, CT 7 min, WD, DM, PFM 15 min, MRI 19 min; and more. WD was found as the best method for most of uses with best accuracy. The CT disposes with almost the same accuracy and allows measurements of specific regions (e.g. particular muscles), as same as MRI, which accuracy is worse though, but it is not harmful. Frustum Sign Model is usable for very fast estimation of limb volume, but with lower accuracy, Disc Model and Partial Frustum Model is useful in cases when Water Displacement cannot be used.

Effective Calibration and Evaluation of Multi-Camera Robotic Head

International Journal of Advanced Computer Science and Applications, 2015

Breath Analysis Using a Time-of-Flight Camera and Pressure Belts

by Ludek Zalud and Jana Kolarova

Artificial organs, Jan 3, 2015

The proper way of breathing is important for everyone. Healthy people often do not follow respira... more The proper way of breathing is important for everyone. Healthy people often do not follow respiration until breathing problems start-during stress or during sport activity in physiological cases. More serious cases are stroke, injury, or surgery of the chest and others. So, learning to breathe correctly and/or breathing diagnosis is considerable for many reasons. Two novel methods of breath analysis suitable for diagnostics and rehabilitation are presented. The first technique utilizes pressure belts fastened to the patient's belly and chest, and the second method relies on a SwissRanger SR-4000 time-of-flight camera. The measurement principles are described together with the advantages and disadvantages of the applied techniques. The SwissRanger camera depth calibration is proposed to facilitate better results during the breath analysis. The methods are tested on a group of students to provide a comparison of their individual performances. As it was demonstrated, presented meth...

ARGOS - ORPHEUS-X2 User Interface

Orpheus reconnaissance robotic system Orpheus-X2 developed at Department of Control and Instrumen... more Orpheus reconnaissance robotic system Orpheus-X2 developed at Department of Control and Instrumentation is described. The paper is focused to ARGOS visualization software system for sensory supported visual telepresence control of mobile robots. The article describes augmented reality part of the system - namely visual telepresence, 2D and 3D proximity scanner data and inertial sensor data presentation. The concept of real video in background of operator's view with a series of Virtual Head-up Displays is presented. Advantages of ARGOS for real- time data fusion of CCD color camera, thremovision and 3D proximity scanner are depicted.

3D proximity scanner integration to rescue robotic system

Orpheus mobile robot is a teleoperated device primarily designed for remote exploration of hazard... more Orpheus mobile robot is a teleoperated device primarily designed for remote exploration of hazardous places and rescue missions. The robot is able to operate both indoors and outdoors, is made to be durable and reliable. The device is controlled through advanced user interface with joystick and head mounted display with inertial head movement sensor. To increase the system's operability in difficult conditions (fog, smoke, dark), 3D proximity scanner controlled by on-board processor through Ethernet connection was integrated to it. The scanner also represents a step towards semi-autonomous mode of the robot.