Multi-rotor Aerial Vehicle Research Articles

Design of multirotor aerial vehicles: A taxonomy based on input allocation

This paper reviews the effect of multirotor aerial vehicle designs on their abilities in terms of tasks and system properties. We propose a general taxonomy to characterize and describe multirotor aerial vehicles and their designs, which we apply exhaustively on the vast literature available. Thanks to the systematic characterization of the designs, we exhibit groups of designs having the same abilities in terms of achievable tasks and system properties. In particular, we organize the literature review based on the number of atomic actuation units and we discuss global properties arising from their choice and spatial distribution in the mechanical designs. Finally, we provide a discussion on the common traits of the designs found in the literature and the main open and future problems.

On the guidance of fully-actuated multirotor aerial vehicles under control allocation constraints using the receding-horizon strategy

The present work is concerned with the wayset-based guidance of a very general class of fully-actuated multirotor aerial vehicles which can be equipped with fixed or vectorable rotors. The problem is tackled by means of a hierarchical guidance and control framework containing two nested loops. For the outer loop, a guidance strategy based on the nonlinear model predictive control paradigm is proposed. It steers the vehicle through a sequence of position-attitude waysets, while guaranteeing the satisfaction of the control allocation constraints. For the inner loop, a single multi-variable inverse-dynamic force–torque control law is designed to stabilize the translational and rotational dynamics, and an optimal control allocator is formulated, by means of a convex program, to distribute the required control efforts among the available actuators. The asymptotic stability of the inner and outer loop, the recursive feasibility of the guidance algorithm, as well as the feasibility of the control allocator are proved to hold. The proposed method is numerically illustrated with a quadrotor containing two-degrees-of-freedom vectorable rotors and shows to be effective to guide the vehicle while respecting all the rotor constraints.

Motor and Perception Constrained NMPC for Torque-Controlled Generic Aerial Vehicles

This letter presents a perception-aware and motor-level non-linear model predictive control scheme for multi-rotor aerial vehicles. Our formulation considers both real actuation limitations of the platform, and realistic perception objectives for the visibility coverage of an environmental feature while performing a reference task. It directly produces the rotor-level (torque) inputs of the platform motors at high frequency, hence it does not require an intermediate unconstrained controller to work. It is also meant to be generic, by covering standard coplanar quadrotors as well as tilted-propeller multi-rotors. We propose an open-source fully onboard implementation of the method, capable of running at 500 Hz under the intermittent and noisy measurements of one or more cameras. The implementation is extensively tested both in simulation and in real experiments with two substantially different multi-rotor platforms, an underactuated and a fully actuated one, both equipped with two cameras, clearly demonstrating the practicability and high performance of the method.

The UJI Aerial Librarian Robot: A Quadcopter for Visual Library Inventory and Book Localisation.

Over time, the field of robotics has provided solutions to automate routine tasks in different scenarios. In particular, libraries are awakening great interest in automated tasks since they are semi-structured environments where machines coexist with humans and several repetitive operations could be automatically performed. In addition, multirotor aerial vehicles have become very popular in many applications over the past decade, however autonomous flight in confined spaces still presents a number of challenges and the use of small drones has not been reported as an automated inventory device within libraries. This paper presents the UJI aerial librarian robot that leverages computer vision techniques to autonomously self-localize and navigate in a library for automated inventory and book localization. A control strategy to navigate along the library bookcases is presented by using visual markers for self-localization during a visual inspection of bookshelves. An image-based book recognition technique is described that combines computer vision techniques to detect the tags on the book spines, followed by an optical character recognizer (OCR) to convert the book code on the tags into text. These data can be used for library inventory. Misplaced books can be automatically detected, and a particular book can be located within the library. Our quadrotor robot was tested in a real library with promising results. The problems encountered and limitation of the system are discussed, along with its relation to similar applications, such as automated inventory in warehouses.

Path Planning Followed by Kinodynamic Smoothing for Multirotor Aerial Vehicles (MAVs)

Any obstacle-free path planning algorithm, in general, gives a sequence of waypoints that connect start and goal positions by a sequence of straight lines, which does not ensure the smoothness and the dynamic feasibility to maneuver the MAV. Kinodynamic-based motion planning is one of the ways to impose dynamic feasibility in planning. However, kinodynamic motion planning is not an optimal solution due to high computational demands for real-time applications. Thus, we explore path planning followed by kinodynamic smoothing while ensuring the dynamic feasibility of MAV. The main difference in the proposed technique is not to use kinodynamic planning when finding a feasible path, but rather to apply kinodynamic smoothing along the obtained feasible path. We have chosen a geometric-based path planning algorithm “RRT*” as the path finding algorithm. In the proposed technique, we modified the original RRT* introducing an adaptive search space and a steering function that helps to increase the consistency of the planner. Moreover, we propose a multiple RRT* that generates a set of desired paths. The optimal path from the generated paths is selected based on a cost function. Afterwards, we apply kinodynamic smoothing that will result in a dynamically feasible as well as obstacle-free path. Thereafter, a b-spline-based trajectory is generated to maneuver the vehicle autonomously in unknown environments. Finally, we have tested the proposed technique in various simulated environments. According to the experiment results, we were able to speed up the path planning task by 1.3 times when using the proposed multiple RRT* over the original RRT*.

Image Guided Visual Tracking Control System for Unmanned Multirotor Aerial Vehicle with Uncertainty

This paper presents a wavelet-based image guided tracking control system for unmanned multirotor aerial vehicle system with the presence of uncertainty. The visual signals for the visual tracking process are developed by using wavelet coefficients. The design uses a multiresolution interaction matrix with half and details images to relate the time-variation of wavelet coefficients with the velocity of the aerial vehicle and controller. The proposed design is evaluated on a virtual quadrotor aerial vehicle system to demonstrate the effectiveness of the wavelet-based visual tracking system without using an image processing unit in the presence of uncertainty. In contrast to the classical visual tracking technique, the wavelet-based method does not require an image processing task.

Extended state observer-based robust control of an omnidirectional quadrotor with tiltable rotors

A quadrotor with tiltable rotors is a kind of omnidirectional multirotor aerial vehicle (MAV) that has demonstrated advantages of decoupling control of position from the control of orientation. However, quadrotors with tiltable rotors usually suffer from Coriolis term, modeling error and external disturbance. To this end, the extended state observer (ESO)-based controller is designed to estimate and compensate for the above adverse effects. Especially, the controller involves position and attitude controller in parallel. The attitude controller is made up of cascade control-loops: an outer quaternion-based attitude control-loop and an inner ESO-based Proportional derivative angular velocity control-loop. Similarly, the position controller consists of an outer proportional position control-loop and an inner ESO-based PD velocity control-loop. Besides, a linear control allocation strategy, which allocates the controller outputs to tilting angles and motor speed directly, is proposed to avoid the nonlinear allocation matrix. Extensive simulations and flight tests are carried out to illustrate the effectiveness and robustness of the proposed ESO-based controller.

Quasi-Steady In-Ground-Effect Model for Single and Multirotor Aerial Vehicles

This Paper presents a new quasi-steady in-ground effect (IGE) model for small multirotor aerial vehicles such as quadcopter unmanned aerial vehicles. The model offers three major advances to the state of the art: 1) predicting the IGE thrust ratio without singularity, 2) relating the strength of the ground effect to the blade geometry (pitch angle, solidity, and radius), and 3) capturing the effect of multirotor configurations. Two IGE coefficients, based on blade element theory, are introduced and then analyzed using the method of images. Additionally, the thrust-loss phenomenon on multirotor IGE is observed and modeled empirically. Experiments are conducted to validate each component of the model, and the results suggest that the model can be used to predict the onset of the IGE for vehicle motion control and planning in the regime where IGE dominates.

Obstacle Magnification for 2-D Collision and Occlusion Avoidance of Autonomous Multirotor Aerial Vehicles

Collision or occlusion avoidance is one of the most important functions of autonomous unmanned vehicles when maneuvering or conducting missions, including monitoring or following targets in environments with various obstacles such as trees and buildings. While considering the minimum distance to obstacles or approximating the shape of obstacles is convenient, incorporating the shape of the original obstacles, sometimes, can provide more effective strategies for collision and occlusion avoidance of obstacles with complex shapes or arrangements. This article presents an obstacle magnification algorithm that magnifies but retains the original shape of the detected obstacles. Two simple parameters can adjust the position and magnification of the virtual obstacles. The simulation and outdoor experimental results for the obstacle magnification, implemented on an onboard embedded system, demonstrate the effectiveness of this concept, which should be useful in various applications for small autonomous multirotor aircrafts.

Nonlinear Model Predictive Control with Enhanced Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs

In this paper, we propose, discuss, and validate an online Nonlinear Model Predictive Control (NMPC) method for multi-rotor aerial systems with arbitrarily positioned and oriented rotors which simultaneously addresses the local reference trajectory planning and tracking problems. This work brings into question some common modeling and control design choices that are typically adopted to guarantee robustness and reliability but which may severely limit the attainable performance. Unlike most of state of the art works, the proposed method takes advantages of a unified nonlinear model which aims to describe the whole robot dynamics by explicitly including a realistic physical description of the actuator dynamics and limitations. As a matter of fact, our solution does not resort to common simplifications such as: (1) linear model approximation, (2) cascaded control paradigm used to decouple the translational and the rotational dynamics of the rigid body, (3) use of low-level reactive trackers for the stabilization of the internal loop, and (4) unconstrained optimization resolution or use of fictitious constraints. More in detail, we consider as control inputs the derivatives of the propeller forces and propose a novel method to suitably identify the actuator limitations by leveraging experimental data. Differently from previous approaches, the constraints of the optimization problem are defined only by the real physics of the actuators, avoiding conservative – and often not physical – input/state saturations which are present, e.g., in cascaded approaches. The control algorithm is implemented using a state-of-the-art Real Time Iteration (RTI) scheme with partial sensitivity update method. The performances of the control system are finally validated by means of real-time simulations and in real experiments, with a large spectrum of heterogeneous multi-rotor systems: an under-actuated quadrotor, a fully-actuated hexarotor, a multi-rotor with orientable propellers, and a multi-rotor with an unexpected rotor failure. To the best of our knowledge, this is the first time that a predictive controller framework with all the valuable aforementioned features is presented and extensively validated in real-time experiments and simulations.

Trajectory Following with a MAV Under Rotor Fault Conditions

Lately, a novel multirotor aerial vehicle capable of handling single rotor failures was presented. When a rotor fails, physically reconfiguring one of the remaining rotors of a hexarotor allows to compensate for maneuverability limitations. In this work, experimental results show the performance of the vehicle in a trajectory-following task in both nominal and fault conditions.

Safe and optimal navigation for autonomous multi-rotor aerial vehicle in a dynamic known environment by a decomposition-coordination method

In this paper, we present a new solution for the Autonomous navigation problem, using a Decomposition-Coordination Method (DCM) 1. The main purpose of this work is to compute an optimal and safe path for the multi-rotor Unmanned Aerial Vehicle (UAV) in a dynamic environment, moving from an initial location to the desired state. We assume that the flight environment is totally known to a supervisory unit, and the positions and trajectories of dynamic obstacles could be known in real-time, thus to perform in such environment a high reactivity is required as well as good connectivity with the supervisory unit that provides the safe path, each time one obstacle or more are detected on the road, so that the UAV could autonomously diverts from the unsafe path to the new safe one, and avoid the potential collisions. First and foremost, we choose a generalized nonlinear model for the multi-rotors in view of the rotational and translational dynamics of the UAV. We then associate that model with the objective functions. After that, we proceed to the resolution of the multi-objective optimization problem using our approach of decomposition-coordination. The principle of this method consists in decomposing the system into several smaller subsystems to simplify the treatment. Then we achieve the coordination afterward using Lagrange multipliers. To prove the convergence and stability of our method we make use of a Lyapunov function chosen particularly for this system. In the last section we present the simulation results, to confirm the reliability of our method.

Fast Nonsingular Terminal Sliding Mode Flight Control for Multirotor Aerial Vehicles

This article is concerned with the robust flight control of multirotor aerial vehicles (MAVs) subject to bounded force and torque disturbances. The focus is on the entire class of MAVs containing an arbitrary even number (≥4) of fixed (not vectoring) rotors. To deal with this problem, first, a ubiquitous hierarchical control architecture in which the attitude control loop is nested inside the position control loop is adopted and augmented with a control allocator which makes the design of the control laws themselves independent of the rotor arrangement. Specially, the control allocation problem is formulated as a quadratic program that minimizes the thrust commands and accounts for the thrust range and rate bounds. Second, geometric attitude and position control laws are designed separately using a multi-input fast nonsingular terminal sliding mode control (FNTSMC) strategy, which guarantees singularity-free finite-time stability and robustness. The main contributions are, first, the augmentation of the hierarchical control scheme for extending its applicability to any fixed-rotor MAV and, second, a detailed geometric design and finite-time stability analysis of the position and attitude control loops using the FNTSMC theory. The system is evaluated on computational simulations as well as on a hardware-in-the-loop experiment, showing that it is effective, simple to implement and adjust, and reliable to operate in nonlinear regimes as well as under bounded disturbances.

Design of an Experimental Test Bench for a UAV Type Convertiplane

This paper deals with the design of a test bench for an unnamed aerial vehicle UAV type convertiplane with controlled electric drives and tilt rotors (propellers) executed on a quadcopter pattern. This experimental test bench provides an intermediate step between simulation process and real time flight of the UAV, it allows to test its and evaluate solutions in safe and controllable environment conditions. Thus, the development of methods of state estimation and control UAV becomes possible, in addition the developed system can be used for teaching about the basis of automatic control in multirotor aerial vehicles. The test bench presented in this paper contains a convertiplane type quadcopter attached on the base through a universal joint which let the UAV be able to rotate around plane axes x and y, while the vertical axis z is fixed, in turn this part of the system is fixed through a bar connected with a linear guideway block that moves over a linear guide which depends of the generated lifting force by the UAV. To determinate the travelled road of the system and the different parameters of the behavior of the convertiplane it has been also implemented a measuring system.

Smart Glove and Hand Gesture-Based Control Interface for Multi-Rotor Aerial Vehicles in a Multi-Subject Environment

This paper introduces an adaptable, human-computer interaction method to control multi-rotor aerial vehicles in unsupervised, multi-subject environments. A region-based convolutional neural network (R-CNN) first detects subjects in a frame and their faces’ regions of interest (RoIs), which are then fed to a facial recognition module to search for the main subject within the frame. The R-CNN model supplies the right-hand RoI of the main subject to a convolutional neural network (CNN) that classifies the right-hand gesture. A motion processing unit (MPU) and four flex sensors are embedded in the left hand’s smart glove to produce discrete and continuous signals. Those signals are generated based on the bending of left-hand fingers and the left hand’s roll angle and then fed to a support vector machine (SVM) to classify the left-hand gesture. Three validation layers have been implemented, including a human-based validation, classification validation, and the system validation. The comprehensive experimental results have validated the proposed method.

Experimental Evaluation of the Shadowing of a Planar Antenna Caused by a Quadcopter Frame

Abstract The use of mobile data transfer can significantly increase the range of the remote-controlled operation of multirotor aerial vehicles. The planar antennas of ready-to-use 3G/LTE cellular communication dongles provide a low-cost and lightweight communication solution. In this paper, antenna shadowing caused by a quadcopter frame is experimentally investigated. The communication module is a 3G/LTE “Huawei 3372h” dongle with two planar built-in antennas and a receiver diversity function. The quadcopter frame is a widely used “F450” with Nylon arms and a PCB centre. It has been found that in order to minimize the antenna shadowing effect, planar antennas should be installed at the bottom of the frame, in parallel with the frame, with an air gap not less than the distance to the outer boundary of the reactive Near Field (NF).

Design, Mathematical Modeling, and Stability of a Reconfigurable Multirotor Aerial Vehicle

AbstractA new design of a reconfigurable multirotor is developed by employing a novel active–passive motor scheme. The scheme is based on quadrotor configuration with four additional motors placed ...

EKF-Based Parameter Identification of Multi-Rotor Unmanned Aerial VehiclesModels.

This work presents a method for estimating the model parameters of multi-rotor unmanned aerial vehicles by means of an extended Kalman filter. Different from test-bed based identification methods, the proposed approach estimates all the model parameters of a multi-rotor aerial vehicle, using a single online estimation process that integrates measurements that can be obtained directly from onboard sensors commonly available in this kind of UAV. In order to develop the proposed method, the observability property of the system is investigated by means of a nonlinear observability analysis. First, the dynamic models of three classes of multi-rotor aerial vehicles are presented. Then, in order to carry out the observability analysis, the state vector is augmented by considering the parameters to be identified as state variables with zero dynamics. From the analysis, the sets of measurements from which the model parameters can be estimated are derived. Furthermore, the necessary conditions that must be satisfied in order to obtain the observability results are given. An extensive set of computer simulations is carried out in order to validate the proposed method. According to the simulation results, it is feasible to estimate all the model parameters of a multi-rotor aerial vehicle in a single estimation process by means of an extended Kalman filter that is updated with measurements obtained directly from the onboard sensors. Furthermore, in order to better validate the proposed method, the model parameters of a custom-built quadrotor were estimated from actual flight log data. The experimental results show that the proposed method is suitable to be practically applied.

Route optimization for multi-rotor aerial vehicles

The mathematical statement of the problem for route optimization of multi-rotor aerial vehicles has been developed. In this formulation, the indicated problem is a Traveling Salesman Problem (TSP) of an asymmetric closed type. As a target functions of optimization the total energy consumption of MRAV motion along the broken line passing through n given points in the order given by the permutation (problem 1) and the total time of flying around the route along a broken line passing through n given points in the order given by the permutation (problem 2) have been proposed. It is shown that when a MRAV DJI Inspire 1 flies around the route points which have different altitudes, the differences between the “intuitive” and the optimal variants can be up to 43%. The more is difference in altitudes of the points to be flied around, the more is the difference between the “intuitive” and the optimal route variants. From practical point of view, the solution to problem 1 can be used in case there is a need to save MRAV power sources for solving some other problems. The solution to problem 1 is needed in case when there is a need for faster flying around the route.On average, the benefit of using optimization for an aerial vehicle of this type is 17-18%.

Image-guided Flight Tracking Control System for Multirotor Aerial Vehicles

Image-guided Flight Tracking Control System for Multirotor Aerial Vehicles