Autonomous wireless self-charging for multi-rotor unmanned aerial vehicles

Rotary-wing unmanned aerial vehicles (UAVs) have the ability to operate in confined spaces and to hover over point of interest, but they have limited flight time and endurance. Conventional contact-based charging system for UAVs has been used, but it requires high landing accuracy for proper docking. Instead of the conventional system, autonomous wireless battery charging system for UAVs in outdoor conditions is proposed in this paper. UAVs can be wirelessly charged using the proposed charging system, regardless of yaw angle between UAVs and wireless charging pad, which can further reduce their control complexity for autonomous landing. The increased overall mission time eventually relaxes the limitations on payload and flight time. In this paper, a cost effective automatic recharging solution for UAVs in outdoor environments is proposed using wireless power transfer (WPT). This research proposes a global positioning system (GPS) and vision-based closed-loop target detection and a tracking system for precise landing of quadcopters in outdoor environments. The system uses the onboard camera to detect the shape, color and position of the defined target in image frame. Based on the offset of the target from the center of the image frame, control commands are generated to track and maintain the center position. Commercially available AR.Drone. was used to demonstrate the proposed concept which is equppied with bottom camera and GPS. Experiments and analyses showed good performance, and about 75% average WPT efficiency was achieved in this research

A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

A cloud robotics architecture for an emergency management and monitoring service in a smart cityenvironment

Cloud robotics is revolutionizing not only the robotics industry but also the ICT world, giving robots more storage and computing capacity, opening new scenarios that blend the physical to the digital world. In this vision new IT architectures are required to manage robots, retrieve data from them and create services to interact with users. In this paper a possible implementation of a cloud robotics architecture for the interaction between users and UAVs is described. Using the latter as monitoring agents, a service for fighting crime in urban environment is proposed, making one step forward towards the idea of smart cit

Mixed marker-based/marker-less visual odometry system for mobile robots

When moving in generic indoor environments, robotic platforms generally rely solely on information provided by onboard sensors to determine their position and orientation. However, the lack of absolute references often leads to the introduction of severe drifts in estimates computed, making autonomous operations really hard to accomplish. This paper proposes a solution to alleviate the impact of the above issues by combining two vision‐based pose estimation techniques working on relative and absolute coordinate systems, respectively. In particular, the unknown ground features in the images that are captured by the vertical camera of a mobile platform are processed by a vision‐based odometry algorithm, which is capable of estimating the relative frame‐to‐frame movements. Then, errors accumulated in the above step are corrected using artificial markers displaced at known positions in the environment. The markers are framed from time to time, which allows the robot to maintain the drifts bounded by additionally providing it with the navigation commands needed for autonomous flight. Accuracy and robustness of the designed technique are demonstrated using an off‐the‐shelf quadrotor via extensive experimental test

The development of an autonomous navigation system with optimal control of an UAV in partly unknown indoor environment

This paper presents an autonomous methodology for a low-cost commercial AR.Drone 2.0 in partly unknown indoor flight using only on-board visual and internal sensing. Novelty lies in: (i) the development of a position estimation method using sensor fusion in a structured environment. This localization method presents how to get the UAV localization states (position and orientation), through a sensor fusion scheme, dealing with data provided by an optical sensor and an inertial measurement unit (IMU). Such a data fusion scheme takes also in to account the time delay present in the camera signal due to the communication protocols; (ii) improved potential field method which is capable of performing obstacle avoiding in an unknown environment and solving the non reachable goal problem; and (iii) the design and implementation of an optimal proportional - integral - derivative (PID) controller based on a novel multi-objective particle swarm optimization with an accelerated update methodology tracking such reference trajectories, thus characterizing a cascade controller. Experimental results validate the effectiveness of the proposed approach

Model predictive cooperative localization control of multiple UAVs using potential function sensor constraints: a workflow to create sensor constraint based potential functions for the control of cooperative localization scenarios with mobile robots.

The global localization of multiple mobile robots can be achieved cost efficiently by localizing one robot globally and the others in relation to it using local sensor data. However, the drawback of this cooperative localization is the requirement of continuous sensor information. Due to a limited sensor perception space, the tracking task to continuously maintain this sensor information is challenging. To address this problem, this contribution is presenting a model predictive control (MPC) approach for such cooperative localization scenarios. In particular, the present work shows a novel workflow to describe sensor limitations with the help of potential functions. In addition, a compact motion model for multi-rotor drones is introduced to achieve MPC real-time capability. The effectiveness of the presented approach is demonstrated in a numerical simulation, an experimental indoor scenario with two quadrotors as well as multiple indoor scenarios of a quadrotor obstacle evasion maneuver

Cooperative Control for Target Tracking with Onboard Sensing

Abstract We consider the cooperative control of a team of robots to estimate the position of a moving target using onboard sensing. In particular, we do not as-sume that the robot positions are known, but estimate their positions using relative onboard sensing. Our probabilistic localization and control method takes into ac-count the motion and sensing capabilities of the individual robots to minimize the expected future uncertainty of the target position. It reasons about multiple possi-ble sensing topologies and incorporates an efficient topology switching technique to generate locally optimal controls in polynomial time complexity. Simulations show the performance of our approach and prove its flexibility to find suitable sensing topologies depending on the limited sensing capabilities of the robots and the movements of the target. Furthermore, we demonstrate the applicability of our method in various experiments with single and multiple quadrotor robots tracking a ground vehicle in an indoor environment

Tag Recognition for Quadcopter Drone Movement

Unmanned Aerial Vehicle (UAV) drone such as Parrot AR.Drone 2.0 is a flying mobile robot which has been popularly researched for the application of search and rescue mission. In this project, Robot Operating System (ROS), a free open source platform for developing robot control software is used to develop a tag recognition program for drone movement. ROS is popular with mobile robotics application development because sensors data transmission for robot control system analysis will be very handy with the use of ROS nodes and packages once the installation and compilation is done correctly. It is expected that the drone can communicate with a laptop via ROS nodes for sensors data transmission which will be further analyzed and processed for the close-loop control system. The developed program consisting of several packages is aimed to demonstrate the recognition of different tags by the drone which will be transformed into a movement command with respect to the tag recognized; in other words, a visual-based navigation program is developed