Autonomous Recharging and Flight Mission Planning for Battery-operated Autonomous Drones

Autonomous drones (also known as unmanned aerial vehicles) are increasingly popular for diverse applications of light-weight delivery and as substitutions of manned operations in remote locations. The computing systems for drones are becoming a new venue for research in cyber-physical systems. Autonomous drones require integrated intelligent decision systems to control and manage their flight missions in the absence of human operators. One of the most crucial aspects of drone mission control and management is related to the optimization of battery lifetime. Typical drones are powered by on-board batteries, with limited capacity. But drones are expected to carry out long missions. Thus, a fully automated management system that can optimize the operations of battery-operated autonomous drones to extend their operation time is highly desirable. This paper presents several contributions to automated management systems for battery-operated drones: (1) We conduct empirical studies to model the battery performance of drones, considering various flight scenarios. (2) We study a joint problem of flight mission planning and recharging optimization for drones with an objective to complete a tour mission for a set of sites of interest in the shortest time. This problem captures diverse applications of delivery and remote operations by drones. (3) We present algorithms for solving the problem of flight mission planning and recharging optimization. We implemented our algorithms in a drone management system, which supports real-time flight path tracking and re-computation in dynamic environments. We evaluated the results of our algorithms using data from empirical studies. (4) To allow fully autonomous recharging of drones, we also develop a robotic charging system prototype that can recharge drones autonomously by our drone management system

Overview of Battery Monitoring and Recharging of Autonomous Mobile Robot

Mobile robots should be capable of operating with a great degree of autonomy to operate in real social environments. Mobile robotic systems draw power from batteries which have a limited power life. This poses a greater challenge for an autonomous robot. Monitoring the status of the battery power in the robot is therefore important for autonomous robotic systems. Docking and recharging are crucial abilities of autonomous mobile robot to ensure its performance. In this paper, the focus of attention is on the significance of power monitoring for long-term operation of autonomous robots and power estimation and auto-recharging. This paper attempts to brief about a literature review of complete solution for docking methods and recharging the battery of a mobile robot. Major progress is being done on both technology and exploitation of docking mechanism and recharging without any human intervention. This review paper gives the overview of related work in terms of immediate challenges for true energy autonomy in mobile robots with respect to battery technology, power estimation and auto recharging

IR Based Auto-Recharging System for Autonomous Mobile Robot

As autonomous mobile robots are progressively utilized for appropriated missions, a significant issue that should be tackled is the autonomous recharging problem. The robots can be recharged by planning and arranging effectively to maximize its working efficiency. This paper presents the implementation of automatic docking robot with docking strategy and recharging capabilities. The robot is programmed using an algorithm which will guide the robot to move around in a square path of 30 inch by 30 inch continuously. While the robot is performing its assigned task, the battery remaining voltage is monitored by voltage detection module. When the battery voltage reaches threshold value of less than 12V, the microcontroller commands the robot to go back to the docking station for recharging autonomously. This system uses IR receiver sensor in front of the robot and IR transmitter sensor near docking station. The active IR transmitter sensor which transmit infrared signal located near docking area serves as landmark in guiding robot towards docking area. The robot scans the transmitted IR signal from the sensor transmitter only when it needs to charge its battery, if detected it will take the path of charging station. Once the robot approaches the charging station with the required orientation, it connects to the supply terminals for charging. The data related to battery charging voltage is transmitted by microcontroller through Bluetooth HC-05 to PLX DAQ software tool in PC stores it in the Excel sheet as the data arrive. Once the battery is fully charged the robot moves back to continue its original task

Safe, Remote-Access Swarm Robotics Research on the Robotarium

This paper describes the development of the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-agent research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium as well as connects these to the particular considerations one must take when making complex hardware remotely accessible. In particular, safety must be built in already at the design phase without overly constraining which coordinated control programs the users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference

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