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The purpose of this paper is to develop a method for a vision-based automatic landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving platform. The landing system must be highly accurate and meet the size, weigh, and power restrictions of a small UAV.

The vision-based landing system consists of a pattern of red markers placed on a moving target, an image processing algorithm for pattern detection, and a servo-control for tracking. The suggested approach uses a color-based object detection and image-based visual servoing.

The developed prototype system has demonstrated the capability of landing within 25 cm of the desired point of touchdown. This auto-landing system is small (100×100 mm), light-weight (100 g), and consumes little power (under 2 W).

The novelty and the main contribution of the suggested approach are a creative combination of work in two fields: image processing and controls as applied to the UAV landing. The developed image processing algorithm has low complexity as compared to other known methods, which allows its implementation on general-purpose low-cost hardware. The theoretical design has been verified systematically via simulations and then outdoors field tests.

The successful application of the group of unmanned aerial vehicles (UAVs) in the tasks of monitoring large areas is becoming a promising direction in modern robotics. This paper aims to study the tasks related to the control of the UAV group while performing a common mission.

This paper discusses the main tasks solved in the process of developing an autonomous UAV group. During the survey, five key tasks of group robotics were investigated, namely, UAV group control, path planning, reconfiguration, task assignment and conflict resolution. Effective methods for solving each problem are presented, and an analysis and comparison of these methods are carried out. Several specifics of various types of UAVs are also described.

The analysis of a number of modern and effective methods showed that decentralized methods have clear advantages over centralized ones, since decentralized methods effectively perform the assigned mission regardless of on the amount of resources used. As for the method of planning the group movement of UAVs, it is worth choosing methods that combine the algorithms of global and local planning. This combination eliminates the possibility of collisions not only with static and dynamic obstacles, but also with other agents of the group.

The results of scientific research progress in the tasks of UAV group control have been summed up.

This paper aims to present a unified motion control scheme for quadcopters which not only solves the point stabilization and trajectory tracking problems but also the path following problem.

The control problem is solved based on the kinematic model of the unmanned aerial vehicles (UAV). Next, a dynamic compensation controller is considered through of a quadcopter-inner-loop system to independently track four velocity commands: forward, lateral, up/downward and heading rate. Stability and robustness of the whole control system are proved through the Lyapunov’s method. To evaluate the controller’s performance, a multi-user application which allows bilateral communication between a ground station and the Phantom 3 PRO quadrotor is developed.

The performance of the proposed unified controller is shown through real experiments for the different motion control objectives: point stabilization, trajectory tracking and path following. The experiments confirm the capability of the unified controller to solve different motion problems by an adequate selection of the control references.

This work proposes the design of three types of motion controllers, which can be switched to comply a task in outdoor. Based on the software development kit provided by the company DJI, an application to get and send data to the UAV is developed. By means of this application, the three tasks are tested and the robustness of the controllers is proved.

The purpose of this study is to design a flight control model for a control surface-less (CSL) tri-tilt-rotor (TTR) unmanned aerial vehicle (UAV) based on a Proportional Integral Derivative (PID) controller to stabilize the altitude and attitude of the UAV subjected to various flying conditions.

First, the proposed UAV with a tilting mechanism is designed and analyzed to obtain the aerodynamic parameters. Second, the dynamics of the proposed UAV are mathematically modeled using Newton-Euler formation. Then, the PID controller is implemented in the simulation model to control flight maneuvers. The model parameters were implemented in a mathematical model to find the system’s stability for various flight conditions. The model was linearized to determine the PID gain values for vertical take-off and landing, cruise and transition mode. The PID controller was tuned to obtain the desired altitude and attitude in a short period. The tuned PID gain values were implemented in the PID controller and the model was simulated.

The main contribution of this study is the mathematical model and controller for a UAV without any control surface and uses only a thrust vector control mechanism which reduces the complexity of the controller. The simulation has been carried out for various flight conditions. The altitude PID controller and the attitude PID controller for CSL-TTR-UAV were tuned to obtain desired altitude and attitude within the optimum duration of 4 s and deviation in the attitude of 8%, which is within the allowable limit of 14%. The findings obtained from the simulation revels that the altitude and attitude control of the CSL-TTR-UAV was achieved by controlling the rpm of the rotor and tilt angle using the PID controller.

A novel CSL TTR UAV mathematical model is developed with a dual tilting mechanism for a tail rotor and single axis tilt for the rotors in the wing. The flight control model controls the UAV without a control surface using a PID controller for the thrust vector mechanism.

The purpose of this paper is to facilitate autonomous landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving/tilting platform using a robust vision-based approach.

Autonomous landing of a multi-rotor UAV on a moving or tilting platform of unknown orientation in a GPS-denied and vision-compromised environment presents a challenge to common autopilot systems. The paper proposes a robust visual data processing system based on targets’ Oriented FAST and Rotated BRIEF features to estimate the UAV’s three-dimensional pose in real time.

The system is able to visually locate and identify the unique landing platform based on a cooperative marker with an error rate of 1° or less for all roll, pitch and yaw angles.

The proposed vision-based system aims at on-board use and increased reliability without a significant change to the computational load of the UAV.

The simplicity of the training procedure gives the process the flexibility needed to use a marker of any unknown/irregular shape or dimension. The process can be easily tweaked to respond to different cooperative markers. The on-board computationally inexpensive process can be added to off-the-shelf autopilots.

The purpose of this study is to provide the full-state mathematical model and devise a nonlinear controller for a balloon-supported unmanned aerial vehicle (BUAV).

Newtonian mechanics is used to establish the nonlinear mathematical model of the proposed vehicle assembly which incorporates the dynamics of both balloon and quadrotor UAV. A controllable form of the nine degrees of freedom model is derived. Backstepping control is designed for the proposed model and simulations are performed to assess the tracking performance of the proposed control.

The results show that the proposed methodology works well for smooth trajectories in presence of wind gusts. Moreover, the final mathematical model is affine and various nonlinear control techniques can be used in the future for improved system performance.

Multi-rotor unmanned aerial vehicles (MUAVs) are equipped with controllers but are constrained by smaller flight endurance and payload carrying capability. On the contrary, lighter than air (LTA) aerial vehicles have longer flight times but have poor control performance for outdoor operations. One of the solutions to achieve better flight endurance and payload carrying capability is to augment the LTA balloon to MUAV. The novelty of this research lies in full-order mathematical modeling along with transformation to controllable form for the BUAV assembly.

This paper aims to address three major issues in the development of a vision‐based navigation system for small unmanned aerial vehicles (UAVs) which can be characterized as follows: technical constraints, robust image feature matching and an efficient and precise method for visual navigation.

The authors present and evaluate methods for their solution such as wireless networked control, highly distinctive feature descriptors (HDF) and a visual odometry system.

Proposed feature descriptors achieve significant improvements in computation time by detaching the explicit scale invariance of the widely used scale invariant feature transform. The feasibility of wireless networked real‐time control for vision‐based navigation is evaluated in terms of latency and data throughput. The visual odometry system uses a single camera to reconstruct the camera path and the structure of the environment, and achieved and error of 1.65 percent w.r.t total path length on a circular trajectory of 9.43 m.

The originality/value lies in the contribution of the presented work to the solution of visual odometry for small unmanned aerial vehicles.

This 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.

The 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.

The 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.

The 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.

The developed approach could be valuable to applications in indoors.

This paper presents a robust obstacle avoidance system and a fast layered path planning algorithm that are easy to be implemented for practical systems.

The purpose of this paper is to present a novel approach to the design of an autonomous Unmanned Aerial Vehicle (UAV) to aid with the internal inspection and classification of tall or large structures. Focusing mainly on the challenge of robustly determining the position and velocity of the UAV, in three dimensional space, using on‐board Simultaneous Localisation and Mapping (SLAM). Although capable of autonomous flight, the UAV is primarily intended for semi‐autonomous operation, where the operator instructs the UAV where to go. However, if communications with the ground station are lost, it can backtrack along its path until communications are re‐established.

A UAV has been designed and built using primarily commercial‐off‐the‐shelf components. Software has been developed to allow the UAV to operate autonomously, using solely the on‐board computer and sensors. It is currently undergoing extensive flight tests to determine the performance and limitations of the system as a whole.

Initial test flights have proven the presented approach and resulting real‐time SLAM algorithms to function robustly in a range of large internals. The paper also briefly discusses the approach used by similar projects and the challenges faced.

The proposed novel algorithms allow for on‐board, real‐time, three‐dimensional SLAM in unknown and unstructured environments on a computationally constrained UAV.