Adam Bondyra

Falcon: A Compact Multirotor Flying Platform with High Load Capability

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.

Performance of Coaxial Propulsion in Design of Multi-rotor UAVs

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.

Thrust estimation by fuzzy modeling of coaxial propulsion unit for multirotor UAVs

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 units 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.

Robust estimation algorithm of altitude and vertical velocity for multirotor UAVs

This paper describes the process of the development and improvement of the altitude and vertical velocity estimation algorithm. The previous method was developed by authors two years back. After a diagnosis of pressure temperature drift caused by the main IMU, the additional barometric sensor was introduced. Based on readings from this reference component, three main modifications were developed to the algorithms structure. In addition, three experimental sequences are presented to compare the previous approach with new ones. Results showed that new methods achieve better performance and are free from pressure drift caused by sensors heating. Decreasing frequency of altitude measurements in Kalman filter resulted in more robust estimates for pressure changes not related to the vertical movement in indoor and outdoor flights. With properly working estimation algorithm, there is a possibility to develop a controller to maintain desired altitude or vertical velocity.

Development of Vertical Movement Controller for Multirotor UAVs

In this paper, a vertical velocity controller for multirotor UAVs is proposed. Based on the previous research, authors developed a model of vertical movement which takes into consideration measurement noises, and designed a simulation that allowed tuning of mentioned controller. As a regulation scheme, a classical PI structure was used. The derivative part was neglected because of high amplitude of noise during harsh touchdowns. Tuning of parameters was achieved by PSO optimisation. Experimental results showed that the selected control structure and its parameters fulfill stated requirements. In addition, developed simulation is adequate to the real platform.

TAPAS: A Robotic Platform for Autonomous Navigation in Outdoor Environments

Nowadays robotic researches are concerned about autonomous and robust operation outdoors in order to perform a variety of practical applications. Therefore, we present a robotic platform TAPAS designed for autonomous navigation in the man-made environments, like parks, and capable of transporting 5 kg payload. The article presents the hardware design and sensory system that allowed to create a fully autonomous vehicle unique due to its low cost, light weight and long battery duration. Presented solution was already thoroughly evaluated at the international robotic competition Robotour 2014, where TAPAS took ex aequo 4th place out of 13 robots. Taking part in the competition provided feedback that is discussed in the article and will be used for further developments.

Exploring OpenStreetMap Publicly Available Information for Autonomous Robot Navigation

Autonomous outdoor navigation had been a topic researched for years, but there is still a lack of affordable robots that can efficiently navigate in man-made outdoor environments. Therefore, we present a navigation method developed for TAPAS robot, which was designed for outdoor perception, localization and navigation using fusion of data from multiple sensors. The novelty of the presented approach lies in the usage of publicly available OpenStreetMap information. The proposed system was used in Robotour 2014 competition and allowed to achieve ex aequo 4th place out of 13 teams. The article contains also the summary of experience gained during the competition and future enhancements that can be applied to proposed solution.

Fault diagnosis and condition monitoring of UAV rotor using signal processing

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.

Cascade control algorithms of position and attitude for multirotor UAV

Control algorithms are essential in multirotor aerial platforms and remain a trending research topic. This paper presents the development process of different cascade controllers for multirotor UAVs. Two main usage areas of this method are described — the control of position and attitude. Based on the literature and experience from previous research, structures of mentioned algorithms are proposed. Adequate data-driven simulation models are formulated and used in the tuning process. Additionally, a customised test bench was constructed and utilised for experiments. Comparison between previous solutions and new control structures is performed in both simulation and field experiments. Better performance, robustness and flexibility of cascade control algorithms are proven on the basis of gathered results.

Experimental Test Bench for Multirotor UAVs

Development of methods of state estimation and control for multirotor micro UAVs is often a long and troublesome process. In many cases, various devices that allow to test and evaluate solutions in safe, controllable environment are used. This paper presents a design of custom test bench for unmanned multirotor aerial vehicles. Developed device provides a intermediate step between simulation phase and test flights, where some of basic properties of flight can be evaluated. Thanks to fixing the vehicle on a triaxial gimbal, it is possible to simulate its behaviour during flight scenarios. Set of precise encoders, mounted on every axis, delivers ground truth data about vehicle’s attitude. Solutions that allow to precisely synchronize data from both sources, the test bench and multirotor’s on-board sensors, are presented. Custom PC software provides functionality of storing and presenting gathered data. The whole systems is a low-cost, easy to replicate solution, with simple components manufactured using FDM 3D printing technology. The test bench has been evaluated as helpful tool in development of various aerial platforms. In addition, the system can serve in teaching the basics of automatic control in aerial vehicles.