Autonomous Battery Charging of Quadcopter

Transcription

1 ECE 4901 Fall 2016 Project Proposal Autonomous Battery Charging of Quadcopter Thomas Baietto Electrical Engineering Gabriel Bautista Computer Engineering Ryan Oldham Electrical Engineering Yifei Song Electrical Engineering Sponsor: Professor Ashwin Dani, Ph.D. Assistant Professor Electrical and Computer Engineering University of Connecticut 347 Fairfield Way, U-4157 ITE-Building Storrs, CT

2 Summary Quadcopters have a limited flight time due to current battery supply limitations. Commercially available quadcopters typically last anywhere from 20 to 30 minutes on a single battery charge. Adding more batteries is not a desirable solution because increasing payload weight will consequently consume more power, ultimately reducing battery life and flight time. Our Design Team plans to develop a UAV system, specifically a quadcopter, which recharges itself without any need for human interaction. For this design project, we plan to develop an autonomous system that can navigate our quadcopter to charging station, charging the quadcopter battery without any human assistance. We have split this design project into two sections. Section one is the software design, which will allow for autonomous flight and docking of our quadcopter with the charging station. The second section is the hardware design that is needed in a charging system that will fully recharge the drones battery in a timely manner. Background Unmanned Aerial Vehicles (UAV) provide aerial surveillance at an affordable cost with easy to learn controls. UAVs have grown increasingly popular over the last decade causing a high demand to continuously improve their functionality. Current UAV technology is severely restricted by battery storage capacity and requires frequent human interaction between sessions to manually recharge a battery. A quadcopter is a class of UAV similar in design to that of a helicopter. Quadcopters are composed of four vertically oriented rotors attached to a frame, each controlled by their own individual motor. Flight is made possible by altering the thrust generated from each rotor according to feedback collected through a collection of sensors and commands. Software can be implemented to automatically send commands to the quadcopter motors based off of the sensory information collected onboard. This automated system can be developed to navigate our quadcopter to a recharging station within a close proximity. The quadcopter will then connect

3 with the recharging station, supplying power to the battery. Finally, after being fully charged, our quadcopter will resume automated flight. An important aspect of our project to consider is the environment that our system will be performing within. Our first test will be completely indoors in an empty room. The quadcopter will be stationed at one end of a room and the charging station will be placed at the other side. The goal is to have the quadcopter successfully locate and dock itself upon the charging station on the opposite side of the room. The drone will then recharge its battery and take off again. All of this will be done without any human interaction. After achieving this first task, we will have successfully developed a platform for further research with an autonomously charging quadcopter in different criteria. That is, we will then have to consider a design that works well with obstacles in the room such as furniture and more importantly a system that cooperates with the weather conditions. For this project to be brought to real world applications, the weather must be considered or the autonomous charging design is useless outdoors. In order to move forward with this design, we will first achieve a fully autonomous battery charging quadcopter system in an empty room indoors. After solving this initial problem, we will then have a platform for future development of a system that works in all environmental conditions. As previously stated, our design is split into a hardware and software section. This will increase our time efficiency by having more specific responsibilities and roles assigned to each individual team member. Software Team Learning and applying Python, the programming language that will be required to design an automated system. Determining the needed sensory information to accomplish an automated flight and navigation procedure. Understanding and applying control commands in ROS (Robotic Operating System) Hardware Team Design of a conductive charging station that will consistently allow our quadcopter to dock.

4 Design and manufacturing of a current and voltage control circuit for both the charging platform and the quadcopter. Any needed modifications to our quadcopter such as additional sensors. Solution To begin this design, our team first needed to select a quadcopter. A comparison was made between 2 drones. Table 1. Comparison chart of AR.Drone and 3DR Key Points Easily modified. Description The A.R. drone is equipped with a removable outer frame and multiple ports for additional sensors. The drone also

5 has many replacement parts commercially available. Good price point. The AR drone is available to use through our sponsor eliminating a need to purchase a drone. Commonly used drone. Because of many third party developers, Parrot launched the AR.Drone open Application Programming Interface (API) game development platform. This open platform allows for creative programming algorithm design. Lightweight and compact The AR drone weighs under a pound and is a relatively compact size (517 x 517 x 127 mm). This lightweight drone allows for a smaller charging station design and will also have less power consumption compared to heavier drones. From table 1, we compared the AR drone 2.0 and 3DR since these two quadcopters are currently available at University of Connecticut. From the chart, we can see that the AR drone 2.0 is lighter and smaller compared to the 3DR. Due to these two characteristics will help us design a smaller charging platform. Since the material of AR drone 2.0 is built by carbon fiber instead of plastic compare to 3DR, it is much more reliable. We decided to use image processing to track the charging station, from the table, the AR drone 2.0 has two internal camera installed already which makes this system possible. So we do not need to use any external cameras for image processing, which the 3DR requires. This will help us decrease the weight on the quadcopter and let the battery last longer. Another important element is the cost of AR Drone is about 300$ compare to 1000$ which will help us keep in the budget.

6 The following limitations need to be realized during the design process. 1. Network Connection. The response time between quadcopter and pc terminal over a network can lead to crippling delays in our system. A wireless network will also be limited in range and 2. Computational Speed. Both quadcopter and pc terminal will have delays in processing information. Image processing can require large amounts of processing power. 3. Stability. The quadcopter will have small unpredicted variances in movement that will inv. 4. Sensor Accuracy. Sensors are designed to operate within certain limits. For example, an acoustic sensor will only pick up on certain sound frequencies and strengths. 5. Charging Time. Current Lithium Polymer battery technology limits the flow of current in and out of the cells. These limits mean battery charging time will be over 2 hours. 6. Weight Capacity. As we increase weight, battery life will decrease as well. 7. Budget. We are limited to roughly $ for any additional parts. Software Technical Design There are different approaches to the software design for a tracking system. The main goal of this tracking system is to simply allow the drone to find the charging station in an empty room and steadily land on it. This system can be broken up into two parts. First we need to find a way to get the quadcopter to find and fly to the general area of the charging station. Once the drone is hovering over the charging station, the second objective is to have it land steadily on it. The quadcopter must autonomously fly to the charging station, dock, and take off once fully charged. In order to achieve autonomous flight, we must write a set of functions for the drone that commands its movement and tracking. These functions will be written in Python using Robot Operating System (ROS) and other packages such as OpenCV for video processing. Autonomous flight will be achieved by letting the drone hover by changing the coordinates of the drone inside a function.

7 Locating the Charging Station One way to locate the rough location of the charging station is to use GPS. The A.R. Drone has an on board GPS system that contains its location. It is possible to obtain a Flight Recorder Module to bring the drone to a specific location on the map. This location can be set to where the charging station is. Another method to locate the charging station is to use image processing. Using different nodes, or functions, the drone will be able to track the charging station and fly over to it. The front camera continually checks for a tag while the drone is autonomously flying. We simply implement algorithms in python and alter parameters to track the specified tag that we want based off shape or color. Once detected, the coordinates of the tag are sent to the drone. The quadcopter will fly over to the station and hover over it. Our team decided to use image processing to locate the charging station. Due to the criteria that the drone will fly indoors without obstacles, we believe that this is the best choice. If this experiment was to take place outside, weather conditions such as snow will affect image processing and another design will need to be considered. However, since the experiment is held inside, GPS is not necessary. We will approach the problem with an image processing method, detecting the color or tag that is near the charging station. The drone will then fly closer to the tag until it arrives at the station. Once the drone has found the charging station, it must dock on top of it in order to charge. In order to do this, the bottom camera of the drone will continuously check for a tag. If the bottom camera detects the docking tag, then the drone will descend onto the charging station and start charging. Another function will continuously check the battery life until it is full. Once it is full the drone will take off again to autonomously fly. Below is a brief visual of how the image tracking system will work.

8 Figure 1. Image processing visual Camera Node: Obtains a video stream from the camera. This is the low level driver to the camera. Visual Perception Node: Extracts a set of pixels defining the object we want to track and publishes the coordinates to the Region of Interest Topic. Head Tracking Node: Computes movement commands that keep the target in the center of the camera s view. These commands are published to the Motor_Commands Topic. Motor Control Node: Subscribes to the Motor_Commands Topic and maps movement commands to be performed by the quadcopter.

9 Charging Station Technical Design In order to begin designing a charging station a design criteria must be established. The design criteria will establish a baseline for determining the optimal method of charging, specifically meeting the goals for this project. The following criteria was determined: Criteria Importance Consistency and Dependability Feasibility An unmanned system will be highly reliant on a dependable docking procedure. Without high consistency and dependability the entire system becomes inoperable. Design should be consistent with expectations. Charging station that is planned using Pseudoscience or unavailable technology can be crippling to our given time frame. Operating Time Design should maximize power transfer to 3 cell LiPo batteries to minimize recharge time. Minimize any additional weight needed on the quadcopter to maximize flight time. Utility System can be operated in different locations and within various scenarios. System should be considered useful and desirable to a consumer. Using our design criteria, a comparison of four possible charging systems was created. Technical details and our approach are also briefly summarized following the chart.

10 Table 2. Comparison of Charging Methods Charging Station Approach Table 2 compared 4 different feasible charging methods. Initially, we considered using Inductive Resonant Charging. Our approach was to design a non-contact charging method that would allow our quadcopter to dependably connect with the station. However, we soon concluded that inductive charging was not practical with our design. Fully charging a 3-cell Lithium Polymer battery would be much greater than 2 hours because of a low efficiency power (~9%) transfer. Additionally power transfer is greatly reduced, cubed related to distance, making any non-contact advantage irrelevant. Battery Swapping System seems like the most effective method but is greatly limited by a few factors. The first factor is the cost of the charging station. LiPo (Lithium Polymer) batteries can are roughly 30 dollars each. If one charging station needs 3 batteries, our design of several charging stations will rapidly increase over our budget limit ($1000). Another important negative aspect of Battery Swapping is the design consists of many moving parts, greatly reducing reliability and requiring Computer Aided Drawing skill sets that our design team does not have. A Capture Latch System is a system that works similar to how a shuttle docks with a space station or a boat docks in a harbor. The main concept behind this method of recharging is stability and connection of our drone. This method would ensure consistent connection between the quadcopter and the charging station but is unnecessary for our predicted application. Capture latch was a debatable choice but for our application we do not expect any situation that requires

11 great stability. The chosen method of charging, conductive, offers the same predicted consistency but simpler in terms of design. Design of the Charging Station Contact plate charging is a universally well known charging method that many of us are familiar with. This method of charging offers a high tolerance for landing error and a predicted high efficiency power transfer. The charging station is predicted to be design as follows: 4 Copper contact plates for the drone to land on 4 Copper contacts attached under each arm of the quadcopter. Small magnets attached with contacts on the quadcopter to to increase stability during landing procedure and to maximize power transfer to increased contact. Wires will be made from this contacts on the quadcopter to the battery. Circuit components to control and regulate the flow of current to the Lithium Polymer batteries will be needed. A Component will need to be attached to the quadcopter. Design of the station framework will be made of plastic and be made to keep quadcopter level while charging.

12 Project Plan Hardware Development Timeline 1. Research Lithium Polymer Battery technology. 2. Develop schematic for a Voltage and Current control circuit on PSPICE. (Early December) 3. Purchase needed circuit components. (December) 4. Breadboard Lab Test. (Mid - Late December) 5. Manufacture Integrated Circuit for system. (January - Early February) 6. Construct Charging Station. (Early February) 7. Field Testing (February) 8. Modifications if Necessary. (Remaining Time) Software Development Timeline (next 2-3 months) 1. Continue going through ROS tutorials 2. Fly drone with simple flight maneuvers in the lab to familiarize us with 3. Control drone in Gazebo simulator with joystick to understand how the drone flys 4. Research blob detection algorithm to implement object tracking 5. Write individual nodes to execute specific tasks 6. Test each node to make sure they are working as they should be Budget For this project, our sponsor is willing to spend 1,000 dollars. The software design requires none of this money because we will be using open source software packages that are free for public use. The AR.Drone is provided by the Department of Electrical and Computer Engineering, thus the only development cost will come from the hardware design of the battery charging station.

13 Item Cost Quantity Total Circuit Components (includes copper wiring) $50 2 $100 Copper conduction plates $20 Cutting a single Plate Into 4 (3 by 3 ) $20 Copper sheet for contacts $10 Single sheet $10 Neodymium magnets $10 Pack of 10 $10 Battery (2200mA) $40 1 $40 PVC for station frame ~ $20 $10 Senors (Acoustic, Infrared, e.g.) ~$40 N/A $50 Replacement parts or tools (miscellaneous) $60 Total Budget ~$300 (Expected) $1000 (Limit) Current budget plans to be well within our given constraints. Our budget was calculated in terms of only completing the project. Further development such as multiple charging stations will lead to an increase in our expected spending. Spending is expected to change as progression is made through the design.