Multirotor Micro Research Articles

A Study on the Effect of Structural Compliance Placing in Soft Contact/Collision Properties of Multirotor Micro Aerial Vehicles

Adding compliance (softness) has been introduced as an effective way to improve the physical collision resilience characteristics of multirotor micro aerial vehicles (MAVs). This article answers the question “Where is the best place to apply compliance in a multirotor MAV to make it more collision‐resilient?” by analyzing the output data of more than 1200 drone collision tests through two sets of accelerated and nonaccelerated collision experiments for four main configurations of micro‐quadcopters each possessing a unique softness layout of physical frame. It is shown that while applying compliance to the protective propeller guards (bumpers) of a micro‐quadcopter provides a more elastic collision, it does not improve its energy‐dissipation (impact damping) characteristics. On the other hand, enhancing the inner frame of the micro‐quadcopter with a softer structure results in higher rates of impact energy damping during the collisions and an increase in the impact time, which results in lower impact accelerations the MAV experiences during the crush. A mathematical model is developed representing the contact/collision interactions as nonlinear viscoelastic forces. Comparing the results of the simulations to the experiments suggests that this model can effectively mimic the impact behavior of contacting/colliding MAVs with different structural stiffness and damping.

Bio-inspired classification and evolution of multirotor Micro Aerial Vehicles (MAVs): A comprehensive review

Multirotor Micro Aerial Vehicles (MAVs) have become essential in many applications like surveillance, disaster management, and aerial inspection. The diverse demands of these applications have led to numerous design innovations, growing the MAV landscape substantially. However, such growth has made it challenging to understand the evolution and classification of MAV designs based on their functions and features. We address this challenge by introducing a novel, bio-inspired taxonomic classification framework for MAVs. Our framework spans six hierarchical ranks, each containing a diverse set of categories that classify MAVs from distinct design perspectives. It enables a proper comparison of the MAV designs in the literature, revealing their key similarities and differences. It also helps to trace the evolution of MAVs over time, identifying research trends and potential gaps. Lastly, it offers insights into future MAV design trajectories, providing a complete and clear understanding of the MAV design landscape.

Development of a solar powered multirotor micro aerial vehicle

Rotary-wing aerial vehicles offer manoeuvrability and vertical take-off and landing (VTOL) advantages over fixed-wing systems. Rotary-wing systems do however have comparatively higher energy demands and consequently shorter flight times and therefore a greater energy dependence over their fixed-wing counterparts. Advances in photovoltaic technologies have resulted in significant increases in the specific power (power-to-weight-ratio) of solar cells enabling the design of solar-powered rotary-wing aircraft, and now micro-sized variants. The micro aerial vehicle (MAV) presented, the Micro Solarcopter, is a 0.15 m ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} 0.15 m ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} 0.02 m solar-rechargeable radio-controlled aircraft. The 0.071 kg aircraft can fly for an average time of 3.5 min, recharge in approximately 68 min under 1000 W/m2 irradiance at 25 °C and can hibernate for 38 days without sunlight. The paper explores the use of commercially available photovoltaic cells for the purpose of increasing the energy autonomy of multi-rotor MAVs, by enabling them to stay out in the field without returning to base for charging. A working prototype has been presented which incorporates a battery management system, automatic power on and off, low-power sleep mode, and first-person-view (FPV) camera.

A Benchmarking Platform and a Control Allocation Method for Improving the Efficiency of Coaxial Rotor Systems

Coaxial rotors used on multirotor Micro Aerial Vehicles (MAVs) are complex aerodynamic systems that are typically treated in a simplified manner, operating in sub-optimal conditions. In this letter, we propose: i) an open-source benchmarking platform for coaxial rotor systems that allows us to analyse and improve their efficiency and ii) a map of the whole actuation domain of coaxial systems based on extensive experimentation. In particular, we test three systems built using off-the-shelf components and different rotor configurations. Results demonstrate the existence of a maximum efficiency boundary, which covers the whole thrust range of each system. We also analyze how this boundary changes with respect to the rotor configuration. We compare it with the performance of coaxial rotors controlled with the current standard method (i.e., equal commands for both rotors). Finally, we propose a control allocation strategy that improves the efficiency of coaxial rotors by up to 11% over the current industry standard. Implementation on an octocopter with four sets of coaxial rotors validates the proposed methods across two different rotor separation designs and two different payload scenarios.

A Monocular SLAM-based Controller for Multirotors with Sensor Faults under Ground Effect.

Multirotor micro air vehicles can operate in complex and confined environments that are otherwise inaccessible to larger drones. Operation in such environments results in airflow interactions between the propellers and proximate surfaces. The most common of these interactions is the ground effect. In addition to the increment in thrust efficiency, this effect disturbs the onboard sensors of the drone. In this paper, we present a fault-tolerant scheme for a multirotor with altitude sensor faults caused by the ground effect. We assume a hierarchical control structure for trajectory tracking. The structure consists of an external Proportional-Derivative controller and an internal Proportional-Integral controller. We consider that the sensor faults occur on the inner loop and counteract them in the outer loop. In a novel approach, we use a metric monocular Simultaneous Localization and Mapping algorithm for detecting internal faults. We design the fault diagnosis scheme as a logical process which depends on the weighted residual. Furthermore, we propose two control strategies for fault mitigation. The first combines the external PD controller and a function of the residual. The second treats the sensor fault as an actuator fault and compensates with a sliding mode action. In either case, we utilize onboard sensors only. Finally, we evaluate the effectiveness of the strategies in simulations and experiments.

A design methodology for quiet and long endurance MAV rotors

Over the last 10 years, the use of micro air vehicles has rapidly covered a broad range of civilian and military applications. While most missions require optimizing the endurance, a growing number of applications also require acoustic covertness. For rotorcraft micro air vehicles, combining endurance and covertness heavily relies on the capability to design new propulsion systems. The present paper aims at describing a complete methodology for designing quiet and efficient micro air vehicle rotors, ranging from preliminary aerodynamic prediction to aeroacoustic optimization to experimental validation. The present approach is suitable for engineering purposes and can be applied to any multirotor micro air vehicle. A fast-response and reliable aerodynamic design method based on the blade-element momentum theory has been used and coupled with an extended acoustic model based on the Ffowcs Williams and Hawkings equation as well as analytical formulations for broadband noise. The aerodynamic and acoustic solvers have been coupled within an optimization tool. Key design parameters include the number of blades, twist and chord distribution along the blade, as well as the choice of an optimal airfoil. An experimental test bench suitable for non-anechoic environment has been developed in order to assess the benefit of the new rotor designs. Optimal rotors can maintain high aerodynamic efficiency and low acoustic signature with noise reductions in the order of 10 dB(A).

Acoustic Sensing From a Multi-Rotor Drone

We propose a time-frequency processing method that localizes and enhances a target sound by exploiting spectral and spatial characteristics of the ego-noise captured by a microphone array mounted on a multi-rotor micro aerial vehicle. We first exploit the time-frequency sparsity of the acoustic signal to estimate at each individual time-frequency bin the local direction of arrival (DOA) of the sound and formulate spatial filters pointing at a set of candidate directions. Then, we combine a kurtosis measure based on the spatial filtering outputs and a histogram measure based on the local DOA estimation to calculate a spatial likelihood function for source localization. Finally, we enhance the target sound by formulating a time-frequency spatial filter pointing at the estimated direction. As the ego-noise generally originates from specific directions, we propose a DOA-weighted spatial likelihood function that improves source localization performance by identifying noiseless sectors in the DOA circle. The DOA weighting scheme localizes the target sound even in extremely low signal-to-noise conditions when the target sound comes from a noiseless sector. We experimentally validate the performance of the proposed method with two array placements.

A survey on stereo vision-based autonomous navigation for multi-rotor MUAVs

SUMMARYThis paper presents an overview of the most recent vision-based multi-rotor micro unmanned aerial vehicles (MUAVs) intended for autonomous navigation using a stereoscopic camera. Drone operation is difficult because pilots need the expertise to fly the drones. Pilots have a limited field of view, and unfortunate situations, such as loss of line of sight or collision with objects such as wires and branches, can happen. Autonomous navigation is an even more difficult challenge than remote control navigation because the drones must make decisions on their own in real time and simultaneously build maps of their surroundings if none is available. Moreover, MUAVs are limited in terms of useful payload capability and energy consumption. Therefore, a drone must be equipped with small sensors, and it must carry low weight. In addition, a drone requires a sufficiently powerful onboard computer so that it can understand its surroundings and navigate accordingly to achieve its goal safely. A stereoscopic camera is considered a suitable sensor because of its three-dimensional (3D) capabilities. Hence, a drone can perform vision-based navigation through object recognition and self-localise inside a map if one is available; otherwise, its autonomous navigation creates a simultaneous localisation and mapping problem.

Hybrid obstacle avoidance system with vision and ultrasonic sensors for multi-rotor MAVs

PurposeThis paper aims to develop an obstacle avoidance system for a multi-rotor micro aerial vehicle (MAV) that flies in indoor environments which usually contain transparent, texture-less or moving objects.Design/methodology/approachThe system adopts a combination of a stereo camera and an ultrasonic sensor to detect obstacles and extracts three-dimensional (3D) point clouds. The obstacle map is built on a coarse global map and updated by local maps generated by the recent 3D point clouds. An efficient layered A* path planning algorithm is also proposed to address the path planning in 3D space for MAVs.FindingsThe authors conducted a lot of experiments in both static and dynamic scenes. The results show that the obstacle avoidance system works reliably even when transparent or texture-less obstacles are present. The layered A* path planning algorithm is much faster than the traditional 3D algorithm and makes the system response quickly when the obstacle map has been changed because of the moving objects.Research limitations/implicationsThe limited field of view of both stereo camera and ultrasonic sensor makes the system need to change heading first before moving side to side or moving backward. But this problem could be addressed when multiple systems are mounted toward different directions on the MAV.Practical implicationsThe developed approach could be valuable to applications in indoors.Originality/valueThis paper presents a robust obstacle avoidance system and a fast layered path planning algorithm that are easy to be implemented for practical systems.

Autonomous Landing of a Multirotor Micro Air Vehicle on a High Velocity Ground Vehicle

While autonomous multirotor micro aerial vehicles (MAVs) are uniquely well suited for certain types of missions benefiting from stationary flight capabilities, their more widespread usage still faces many hurdles, due in particular to their limited range and the difficulty of fully automating the deployment and retrieval. In this paper we address these issues by solving the problem of the automated landing of a quadcopter on a ground vehicle moving at relatively high speed. We present our system architecture, including the structure of our Kalman filter for the estimation of the relative position and velocity between the quadcopter and the landing pad, as well as our controller design for the full rendezvous and landing maneuvers. The system is experimentally validated by successfully landing in multiple trials a commercial quadcopter on the roof of a car moving at speeds of up to 50 km/h.

ROBUST HOVERING CONTROLLER FOR UNCERTAIN MULTIROTOR MICRO AERIAL VEHICLES (MAVS) IN GPS-DENIED ENVIRONMENTS: IMAGE-BASED

This paper proposes an image-based robust hovering controller for multirotor micro aerial vehicles (MAVs) in GPS-denied environments. The proposed controller is robust against the effects of multiple uncertainties in angular dynamics of vehicle which contain external disturbances, nonlinear dynamics, coupling, and parametric uncertainties. Based on visual features extracted from the image, the proposed controller is capable of controlling the pose (position and orientation) of the multirotor relative to the fixed-target. The proposed controller scheme consists of two parts: a spherical image-based visual servoing (IBVS) and a robust flight controller for velocity and attitude control loops. A robust compensator based on a second order robust filter is utilized in the robust flight control design to improve the robustness of the multirotor when subject to multiple uncertainties. Compared to other methods, the proposed method is robust against multiple uncertainties and does not need to keep the features in the field of view. The simulation results prove the effectiveness and robustness of the proposed controller.

Modeling and Real-timecontrol of MAV with Multi-rotors

We introduce one configuration of a multi rotor Micro Aerial Vehicle (MAV) composed of six rotors. Accurate modeling and robust flight control of the SixRotor MAV are discussed in this work. Rigorous dynamic model of the SixRotor MAV is obtained both in reference and body frame coordinate systems. The main characteristic of this configuration is the gyroscopic effects and aerodynamic torques tend to be cancelled in the trimmed flight due to the unique mechanical structure, and the attitude and translation dynamics are decoupled which is benefit for designing the control scheme. A disturbance compensator based controller using the derived dynamic models is proposed here for robust hovering control. The disturbance compensator based controller designed by regarding the inaccurate part of the model and sensor noises as disturbances. The validity of the proposed control method has been verified through real-time experiments. The experimental results show that the performance of disturbance compensator based controller performs very well under sensor noise and external disturbances, and have more superiority than traditional PID controller.

UAV APPLICATION IN POST – SEISMIC ENVIRONMENT

Abstract. On April 6, 2009, an earthquake of 6.3 magnitude struck central Italy with its epicentre near L'Aquila, at 42.3502° N, 13.3762° E. The earthquake damaged 3000 to 11 000 buildings in the medieval city of L'Aquila. Several buildings totally collapsed, 308 people were killed. The post emergency phase till now is just at its beginning step. Conventional surveying techniques using high precision total stations, GNSS receivers and laser scanners for investigations on damaged buildings are always becoming more automated, accurate and operative and even much more fast. Even if these techniques represent instruments of extreme operability there are still many evident limits on their use, especially regarding the survey of both the roofs and the facades of tall buildings or dangerous places, typical on post earthquake situations. So using micro UAVs for surveying in such particular cases, many of these problems can be easily bypassed. In fact, the present work aims on experimenting using multi-rotor micro UAVs, that will allow high quality image capturing on roofs and facades of structures in the old city center of L'Aquila. To obtain actual stereoscopic acquisitions of buildings some conditions on the geometry of acquisition have to be observed, for this reason, taking as a guideline classic flight photogrammetric, a flight planning software was developed. Accurate planning for UAVs acquisitions is very important also considering the reduced autonomy of such vehicles. This can be a strategic point if we want to use UAVs for early damage assessment and also for post event reconstruction planning.

AN ACCURACY ASSESSMENT OF GEOREFERENCED POINT CLOUDS PRODUCED VIA MULTI-VIEW STEREO TECHNIQUES APPLIED TO IMAGERY ACQUIRED VIA UNMANNED AERIAL VEHICLE

Abstract. Low-cost Unmanned Aerial Vehicles (UAVs) are becoming viable environmental remote sensing tools. Sensor and battery technology is expanding the data capture opportunities. The UAV, as a close range remote sensing platform, can capture high resolution photography on-demand. This imagery can be used to produce dense point clouds using multi-view stereopsis techniques (MVS) combining computer vision and photogrammetry. This study examines point clouds produced using MVS techniques applied to UAV and terrestrial photography. A multi-rotor micro UAV acquired aerial imagery from a altitude of approximately 30–40 m. The point clouds produced are extremely dense (<1–3 cm point spacing) and provide a detailed record of the surface in the study area, a 70 m section of sheltered coastline in southeast Tasmania. Areas with little surface texture were not well captured, similarly, areas with complex geometry such as grass tussocks and woody scrub were not well mapped. The process fails to penetrate vegetation, but extracts very detailed terrain in unvegetated areas. Initially the point clouds are in an arbitrary coordinate system and need to be georeferenced. A Helmert transformation is applied based on matching ground control points (GCPs) identified in the point clouds to GCPs surveying with differential GPS. These point clouds can be used, alongside laser scanning and more traditional techniques, to provide very detailed and precise representations of a range of landscapes at key moments. There are many potential applications for the UAV-MVS technique, including coastal erosion and accretion monitoring, mine surveying and other environmental monitoring applications. For the generated point clouds to be used in spatial applications they need to be converted to surface models that reduce dataset size without loosing too much detail. Triangulated meshes are one option, another is Poisson Surface Reconstruction. This latter option makes use of point normal data and produces a surface representation at greater detail than previously obtainable. This study will visualise and compare the two surface representations by comparing clouds created from terrestrial MVS (T-MVS) and UAV-MVS.