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Author

Stanisław Gardecki

Bio: Stanisław Gardecki is an academic researcher from Poznań University of Technology. The author has contributed to research in topics: Multirotor & Kalman filter. The author has an hindex of 7, co-authored 20 publications receiving 132 citations.

Papers
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Proceedings ArticleDOI
01 Sep 2017
TL;DR: A three-stage algorithm based on the signal processing and machine learning to detect the occurrence of rotor fault, determine its scale and type and is verified in series of experiments proving its effectiveness.
Abstract: In this paper, a method for fault detection of physical impairment of UAV rotor blades is presented. Actuators in multirotor UAV (Unmanned Aerial Vehicle) systems are common subjects fault diagnosis methods which are an essential part of the active fault-tolerant control scheme. Defects in a propulsion system of the aerial vehicle lead to the loss of thrust generated by rotors and as a result, to the disturbance of thrust balance, higher power consumption and further degradation resulting in the possible crash of the vehicle. Authors propose a three-stage algorithm based on the signal processing and machine learning to detect the occurrence of rotor fault, determine its scale and type. The method is based on measurements of acceleration from the onboard IMU (Inertial Measurement Unit) sensor as unbalanced rotating parts commonly cause vibrations in mechanical systems. The acceleration signal is stored in a cyclic buffer and then processed by simple feature extraction algorithms in order to obtain a characteristic signature of the faulty state. Three different methods of feature extraction are considered in this article, along with the analysis of variable buffer length. Next, the Support Vector Machine (SVM) classifier is used to determine the occurrence and character of the rotor fault. The presented solution was verified in series of experiments proving its effectiveness. In addition, such approach based on signal processing is very versatile and easy to implement in arbitrary flight controller.

37 citations

Book ChapterDOI
02 Mar 2016
TL;DR: Experimental verification of performance of X8 quadrocopter propulsion system in practical terms of designing multi rotor platforms, comparing to design with 8 isolated propulsion units is presented and its advantages versus classic quadrotor concept is shown.
Abstract: There are many different types of propulsion systems developed for multi rotor UAVs. One of the most interesting designs is so called X8 quadrocopter, which extends original quadrotor concept to 8 motors, arranged in 4 coaxial pairs. The advantage of this solution is increased lift of platform, with reasonable volume of platform kept. However, this design suffers from the loss of efficiency due to coaxial propellers’ configuration, because the lower propeller loses thrust working in prop wash of upper propeller. This paper presents the experimental verification of performance of such propulsion system in practical terms of designing multi rotor platforms, comparing to design with 8 isolated propulsion units. In addition, its advantages versus classic quadrotor concept is shown. The series of experiments with different motors and sizes of propellers were conducted to estimate efficiency of coaxial propulsion regarding useful thrust generated by each configuration.

31 citations

Book ChapterDOI
01 Jan 2014
TL;DR: The results of tests of the Kalman filter algorithm on real flying robot proved that estimates calculated with this method are precise and noise resistant.
Abstract: Knowledge about precise robot localization is a key ingredient in controlling it, but the task is not trivial without any visual or GPS feedback. In this paper, authors concentrate on estimation of information about the robot’s altitude. One of the ways to acquire it, is a barometer. This type of sensor returns atmospheric pressure from which the height above the sea level can be computed. These readings have some disadvantages e.i.: vulnerability to pressure jumps and temperature drift as well as delay on the output. These problems can be solved by using Kalman filter algorithm for estimating altitude and vertical velocity, based not only on barometer readings, but also on accelerometer data. In the paper, derivation of the Kalman equations for the process to estimated are shown. Also improvements of the algorithm are described. The results of tests of this algorithm on real flying robot proved that estimates calculated with this method are precise and noise resistant.

21 citations

Book ChapterDOI
01 Jan 2015
TL;DR: The multirotor flying platform Falcon is presented, aimed to provide versatile, multipurpose research platform with high payload capabilities, maintaining compact dimensions and simple, reliable mechanical design.
Abstract: Multirotor flying platforms are very popular research subjects in the field of robotics. However, there are some major disadvantages for this type of vehicles, such as limited flight time, insufficient lifting capability and reduced range of operation. In this paper, the multirotor flying platform Falcon is presented. Its design is aimed to provide versatile, multipurpose research platform with high payload capabilities, maintaining compact dimensions and simple, reliable mechanical design. Presented platform was evaluated in various scenarios performing both autonomous and semi-autonomous flights.

12 citations

Proceedings ArticleDOI
01 Sep 2016
TL;DR: A fuzzy model was chosen for implementation taking into consideration a computational complexity benchmark and promising results of experimental studies open the way for possible applications of the presented method, such as expanding estimation algorithms of attitude and vertical velocity or improvement of the mathematical model.
Abstract: In this paper, a simple and easily applicable model of the coaxial propulsion unit for multirotor UAVs is presented. Measurements performed on the experimental test bench provided information about the generated thrust in relation to PWM control signals and supply voltage. Modelling techniques based on Takagi-Sugeno fuzzy interface and surface fitting are proposed. Implementation of the first order inertial element with the varying time constant allows to consider the propulsion unit's dynamics. A fuzzy model was chosen for implementation taking into consideration a computational complexity benchmark. Fusion of four independent models provides information about a total thrust generated by the physical platform during real flight scenarios. Promising results of experimental studies open the way for possible applications of the presented method, such as expanding estimation algorithms of attitude and vertical velocity or improvement of the mathematical model.

10 citations


Cited by
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01 Jan 2006

384 citations

Journal ArticleDOI
20 Jul 2019-Robotics
TL;DR: A model based on artificial neural network algorithms was built to detect unbalanced blades in a UAV propeller and showed high accuracy, indicating a high number of correct detections and suggests the adoption of this tool to verify the operating conditions of a Uav.

84 citations

Journal ArticleDOI
TL;DR: This paper ends with a quantitative comparison of the performance of motion mode recognition modules developed by researchers in different domains.
Abstract: Recognition of the mode of motion or mode of transit of the user or platform carrying a device is needed in portable navigation, as well as other technological domains An extensive survey on motion mode recognition approaches is provided in this survey paper The survey compares and describes motion mode recognition approaches from different viewpoints: usability and convenience, types of devices in terms of setup mounting and data acquisition, various types of sensors used, signal processing methods employed, features extracted, and classification techniques This paper ends with a quantitative comparison of the performance of motion mode recognition modules developed by researchers in different domains

69 citations

Journal ArticleDOI
TL;DR: This paper thoroughly evaluates the performance of the orientation estimation mechanism available in the Android OS, and the proposed alternative solutions on an unique dataset gathered using an actual smartphone, and draws the conclusions as to the best performing algorithm.
Abstract: Consumer electronics mobile devices, such as smartphones or tablets, are rapidly growing in computing power and are equipped with an increasing number of sensors. This enables to use a present-day mobile device as a viable platform for computation-intensive, real-time applications in navigation and guidance. In this paper, we present a study on the performance of the orientation estimation based on the data acquired by the accelerometer, magnetometer, and gyroscope in a mobile device. Reliable orientation estimation based on the readouts from inertial sensors may be used in more complex systems, e.g., to correct the orientation error of a visual odometry system. We present a rigorous derivation of the mathematical estimation model, and we thoroughly evaluate the performance of the orientation estimation mechanism available in the Android OS, and the proposed alternative solutions on an unique dataset gathered using an actual smartphone. From the experimental results, we draw the conclusions as to the best performing algorithm, and then we evaluate its execution time on Android-based devices to demonstrate the possibility of real-time usage. The Android code for the proposed orientation estimation system is made publicly available for scientific and commercial applications.

47 citations