{"id":20,"date":"2015-09-10T15:36:57","date_gmt":"2015-09-10T19:36:57","guid":{"rendered":"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/?page_id=20"},"modified":"2016-05-06T18:53:15","modified_gmt":"2016-05-06T22:53:15","slug":"systems-engineering","status":"publish","type":"page","link":"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/systems-engineering\/","title":{"rendered":"Systems Engineering"},"content":{"rendered":"<p><strong>1. System summary<\/strong><\/p>\n<p>With a surge in e-commerce logistics, more efficient package delivery mechanisms are required\u00a0to\u00a0deliver more packages in less time at a smaller cost. A hybrid-vehicle autonomous delivery system\u00a0which uses both Autonomous Ground Vehicles and Unmanned Aerial Vehicles can be time efficient\u00a0while maintaining the cost for delivery. The major problem with delivering packages using UAVs is\u00a0robustly navigating to the correct house and dropping the package at an accessible drop zone (like the\u00a0front door), without harming humans or damaging property.<\/p>\n<p>This project aims to solve the problem of efficiently navigating to a house and robustly detecting and\u00a0landing at the drop zone, while avoiding obstacles. The UAV shall be able to take off and land at any\u00a0visually marked platform, enabling it to be used in conjunction with ground vehicles for hybrid delivery\u00a0systems.<\/p>\n<p>This page contains the following items:<\/p>\n<ul>\n<li><a href=\"#problemdescription\">Problem Description<\/a><\/li>\n<li><a href=\"#usecase\">Use Case<\/a><\/li>\n<li><a href=\"#systemrequirements\">System Requirements<\/a><\/li>\n<li><a href=\"#functionalarchitecture\">Functional Architecture<\/a><\/li>\n<li><a href=\"#cyberphysicalarchitecture\">Cyberphysical Architecture<\/a><\/li>\n<li><a href=\"#systemperformance\">System Performance<\/a><\/li>\n<\/ul>\n<div id=\"attachment_98\" style=\"width: 1034px\" class=\"wp-caption aligncenter\"><a href=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/SAM_1550.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-98\" class=\"size-large wp-image-98\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/SAM_1550-1024x685.jpg\" alt=\"SAMSUNG CSC\" width=\"1024\" height=\"685\" \/><\/a><p id=\"caption-attachment-98\" class=\"wp-caption-text\">Artist Concept of Drone Delivery<\/p><\/div>\n<p><a name=\"problemdescription\"><\/a><br \/>\n<strong><em>a. Problem description:<\/em><\/strong><\/p>\n<p>&nbsp;<\/p>\n<p>Currently, package delivery truck drivers hand-carry packages door to door. This model is used by Federal Express (FedEx), United Postal Service (UPS), United States Postal Service (USPS), and Deutsche Post DHL Group (DHL). We believe that drones have the potential to expedite this system.<\/p>\n<p>Amazon is developing Prime Air with the same intent. However, we believe the most efficient system combines delivery trucks with Unmanned Aerial Vehicles (UAV\u2019s) which saves time, expense, and improves customer\u2019s satisfaction.<\/p>\n<p>Project Pegasus aims to deliver packages to a house using UAVs.<\/p>\n<p>Given the coordinates of the house, a UAV with a package takes off from point A, autonomously reaches\u00a0close to the house, scans the outside of the house for a visually marked drop point, lands, drops off the\u00a0package, then takes off again to land on another platform at point B.<\/p>\n<p><a name=\"usecase\"><\/a><strong><em>b.<\/em> <em>Use case<\/em><\/strong><\/p>\n<p>Sam drives a package delivery truck for one of the largest parcel delivery companies. He arrives each morning to a pre-loaded truck and is handed his route for the day. Even though he has an assigned route, he sometimes is tasked with delivery packages to additional streets. These are often the packages that should have been delivered the day before. Thus it\u2019s critical that packages make it to the right house on time today.<\/p>\n<p>Now that his company uses drones, Sam can cover more area in less time. He drives out to his first neighborhood for the day with two packages to deliver. He can quickly deliver the first package, which is heavier. The second package is lighter but a street over. After parking, he quickly attaches the second package to a drone and selects the address on the base station computer. The drone takes off and disappears over a rooftop as Sam unloads the first package.<\/p>\n<div id=\"attachment_165\" style=\"width: 1034px\" class=\"wp-caption aligncenter\"><a href=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Sam.png\" rel=\"attachment wp-att-165\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-165\" class=\"wp-image-165 size-large\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Sam-1024x683.png\" alt=\"Artist Rendition of Sam and one of his drones\" width=\"1024\" height=\"683\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Sam-1024x683.png 1024w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Sam-300x200.png 300w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Sam-768x512.png 768w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><p id=\"caption-attachment-165\" class=\"wp-caption-text\">Artist Rendition of Sam and one of his drones<\/p><\/div>\n<p>Having delivered the first package, Sam gets back in the truck and starts driving. In the past, he would have driven to the next house and dropped off the package. Nowadays, Sam knows that the drone will deliver the package to the right house and catch up. This saves him a few minutes which adds up over the course of the day to real time savings. This makes Sam a little happy.<\/p>\n<p>Meanwhile, the drone has moved within vicinity of the second house. It begins scanning around for the visual marker outside the house. The drone finds the marker and moves in for a landing. It\u2019s able to avoid people on the sidewalk and the large tree outside the house. The drone lands on the marker and does a quick confirmation, it checks the RFID code embedded in the marker. Confirming the correct house has been found, the drone releases the package and notifies the package delivery truck\u2019s base station. The base station then updates the drone on the delivery truck\u2019s position.<\/p>\n<p>The drone catches up to Sam at a red light and they continue on their way. Sam\u2019s day continues this way.<\/p>\n<p>On a major street, he has several packages to deliver in the area. He quickly loads up a few drones, selects the addresses, and watches to drones do all the work. Sam had to get a gym membership since he\u2019s no longer walking as much, but he\u2019s happy to be getting through neighborhoods substantially faster. Because the drones allow one driver to do more, the delivery company is able to offer package delivery at a more competitive rate with more margin. This makes customers happy in addition to getting their packages faster. In turn, they are more likely to use the delivery company, which makes the company pleased with their investment.<\/p>\n<p>Late in the day, the base station on Sam\u2019s delivery truck notifies him that an adjacent route wasn\u2019t able to deliver a package. In the past, this would have meant that the package would be driven back to the warehouse to be resorted and delivered with tomorrow\u2019s load. This was a substantial waste of fuel and manpower. Today, routes can be dynamically updated. A drone will deliver the package to Sam\u2019s truck and once he\u2019s in the correct area, the drone will deliver the package. The customer will never know there was a problem, and the delivery company saves money.<\/p>\n<div id=\"attachment_166\" style=\"width: 934px\" class=\"wp-caption aligncenter\"><a href=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Full-Scope-of-Delivery-System.jpg\" rel=\"attachment wp-att-166\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-166\" class=\"wp-image-166 size-full\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Full-Scope-of-Delivery-System.jpg\" alt=\"Full Scope of Delivery System\" width=\"924\" height=\"504\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Full-Scope-of-Delivery-System.jpg 924w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Full-Scope-of-Delivery-System-300x164.jpg 300w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Full-Scope-of-Delivery-System-768x419.jpg 768w\" sizes=\"auto, (max-width: 924px) 100vw, 924px\" \/><\/a><p id=\"caption-attachment-166\" class=\"wp-caption-text\">Full Scope of Delivery System<\/p><\/div>\n<p>Sam arrives back at the warehouse, his truck empty. He\u2019s satisfied in the work he\u2019s accomplished, customers are happy that received their packages on time, and the delivery company is exceptionally happy with the improved efficiency and customer retention.<\/p>\n<p>&nbsp;<\/p>\n<p><a name=\"systemdesign\"><\/a><strong>2. System design<\/strong><\/p>\n<p><a name=\"systemrequirements\"><\/a><strong>a. System requirements<\/strong><\/p>\n<p>The critical requirements for this project are listed below under <em>Mandatory Requirements<\/em>. These are the \u2018needs\u2019 of the project. Additionally, the team identified several value-added requirements during brainstorming. These \u2018wants\u2019 are listed below under <em>Desired Requirements<\/em>.<\/p>\n<p><strong><em>Mandatory<\/em><\/strong><\/p>\n<p><strong>Functional Requirements<\/strong><br \/>\nM.F.1 Hold and carry packages.<br \/>\nM.F.2 Autonomously take off from a visually marked platform.<br \/>\nM.F.3 Navigate to a known position close to the house.<br \/>\nM.F.4 Detect and navigate to the drop point at the house.<br \/>\nM.F.5 Land at visually marked drop point.<br \/>\nM.F.6 Drop package within 2m of the target drop point.<br \/>\nM.F.7 Take off, fly back to and land at another visually marked platform.<\/p>\n<p><strong>Non-Functional Requirements<\/strong><br \/>\nM.N.1 Operates in an outdoor environment.<br \/>\nM.N.2 Operates in a semi-known map. The GPS position of the house is known, but the exact location of the visual marker is unknown and is detected on the fly.<br \/>\nM.N.3 Avoids static obstacles.<br \/>\nM.N.4 Sub-systems should be well documented and scalable.<br \/>\nM.N.5 UAV should be small enough to operate in residential environments.<br \/>\nM.N.6 Package should weigh at most 100g and fit in a cuboid of dimensions 9.5&#8243; X 6.5&#8243; x 2.2&#8243;.<\/p>\n<p>&nbsp;<\/p>\n<p><strong><em>Desired<\/em><\/strong><\/p>\n<p><strong>Functional Requirements<\/strong><br \/>\nD.F.1 Pick up packages.<br \/>\nD.F.2 Simulation with multiple UAVs and ground vehicles.<br \/>\nD.F.3 Ground vehicle drives autonomously.<br \/>\nD.F.4 UAV and ground vehicle communicate continuously.<br \/>\nD.F.5 UAV confirms the identity of the house before dropping the package (RFID Tags).<\/p>\n<p>D.F.6 Takes coordinates as input from the user.<br \/>\nD.F.7 Communicates with platform to receive GPS updates (intermittently).<\/p>\n<p><strong>Non-Functional Requirements<\/strong><br \/>\nD.N.1 Operates in rains and snow.<br \/>\nD.N.2 Avoids dynamic obstacles<br \/>\nD.N.3 Operates without a GPS system.<br \/>\nD.N.4 Has multiple UAVs to demonstrate efficiency and scalability.<br \/>\nD.N.5 Compatible with higher weights of packages and greater variations in sizes.<br \/>\nD.N.6 Obstacles with a cross section of 0.5m x 0.5m are detected and actively avoided.<br \/>\nD.N.7 A landing column with 2m radius exists around the visual marker<\/p>\n<p>D.N.8 &#8211; Not reliant on GPS. Uses GPS to navigate close to the house. Does not rely on GPS to detect the visual marker at the drop point.<\/p>\n<p>&nbsp;<\/p>\n<p><strong><em>Performance Requirements<\/em><\/strong><\/p>\n<p>P.1 UAV places the package within 2m of the target drop point.<br \/>\nP.2 UAV flies for at least 10 mins without replacing batteries.<br \/>\nP.3 UAV carries packages weighing at least 400g.<br \/>\nP.4 UAV carries packages that fit in a cube of 30cm x 30cm x 20cm.<br \/>\nP.5 One visual markers exists per house.<br \/>\nP.6 Visual markers between houses are at least 10m apart.<br \/>\nP.7. A landing column with 3m radius exists around the visual marker<br \/>\nP.8 Obstacles with a minimum cross section of 1.5m x 0.5m are detected and actively avoided.<\/p>\n<p><strong>Subsystem Requirements<\/strong><\/p>\n<p><strong>S.1 Vision<\/strong><br \/>\nS.1.1 The size of the marker must be within a square of side 1.5m.<br \/>\nS.1.2 Error in the X,Y,Z position of the marker from the camera should be correct upto 10% of distance from it.<br \/>\n<strong>S.2 Obstacle Detection and Avoidance<\/strong><br \/>\nS.2.1 Obstacles must be detected with a range of 50 cm to 150 cm from the UAV.<br \/>\nS.2.2 Obstacles should be at least in 90% of the situations\/positions.<br \/>\nS.2.3 Distance to the obstacle should be correct with a maximum error of 20cm.<br \/>\nS.2.4 Natural obstacles around a residential neighborhood should be detected.<\/p>\n<p><strong>S.3 Flight control<\/strong><br \/>\nS.3.1 UAV must reach the GPS waypoint with a maximum error of 3m.<br \/>\nS.3.2 UAV should be able to fly 10 minutes without replacing the batteries.<\/p>\n<p>&nbsp;<\/p>\n<p><a name=\"functionalarchitecture\"><\/a><strong>b. Functional architecture<\/strong><\/p>\n<p><a href=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Functional-Architecture-v3-Full.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-468 size-large\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Functional-Architecture-v3-Full-1024x399.png\" alt=\"Functional Architecture v3 Final\" width=\"1024\" height=\"399\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Functional-Architecture-v3-Full-1024x399.png 1024w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Functional-Architecture-v3-Full-300x117.png 300w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Functional-Architecture-v3-Full-768x300.png 768w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><\/p>\n<p>Viewing the whole system as a\u00a0black-box, there are 2 inputs \u2013 the package to be delivered and GPS coordinates of customer location. The\u00a0output of the system is the package successfully delivered at the destination.<br \/>\nLooking inside the black box now, the UAV initially holds the package by activating an electro-\u00a0permanent magnet. Coordinates of the customer \u00a0location are input to the User Interface. The developed\u00a0Plan Mission software decides the navigation waypoints and plans a path to the destination. This\u00a0information is then relayed to the UAV by the communication interface. The mission planning software\u00a0continuously receives the current coordinates from the UAV and sends updated coordinates back to the\u00a0UAV.<br \/>\nMeanwhile the UAV checks the battery status. If there is sufficient battery, the UAV arms the motor and\u00a0takes off. The UAV navigates using the waypoint to the vicinity of the destination using GPS input. It\u00a0then switches to the marker detection code. The UAV takes input from the camera and starts to scan the\u00a0vicinity of the customer destination for the marker put up by the customer. It moves in a predetermined\u00a0trajectory for scanning. Once the marker is \u00a0detected the vision algorithm maps the size of the marker in\u00a0the image to actual distance of the UAV from the marker. The UAV continuously receives this\u00a0information and moves towards the marker. The UAV finally lowers lands on the marker. It drops the\u00a0package by disengaging the electro-permanent magnet and flies back to the base station using waypoint\u00a0navigation.<br \/>\nDuring the \u2018Detect Marker\u2019 &amp;\u2019 Navigate to Marker\u2019 functions, the UAV continuously runs an obstacle\u00a0avoidance algorithm on-board. The obstacle-avoidance algorithm continuously receives data from\u00a0sensors, fuses the data and asks the flight controller to alter its trajectory if there is an obstacle in its path.<\/p>\n<p>&nbsp;<\/p>\n<p><a name=\"cyberphysicalarchitecture\"><\/a><strong>c. Cyberphysical architecture<\/strong><\/p>\n<p>The cyberphysical architecture can best be understood by the figure below. On a high level, the system can be broken down into three major categories: mechanical components, electrical components, and software. The electrical components are the bridge between the software and the mechanical actuation.<\/p>\n<p><a href=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Cyberphysical-Architecture-v3-Full.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-469\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Cyberphysical-Architecture-v3-Full.png\" alt=\"Cyberphysical Architecture v3 Final\" width=\"796\" height=\"673\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Cyberphysical-Architecture-v3-Full.png 796w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Cyberphysical-Architecture-v3-Full-300x254.png 300w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Cyberphysical-Architecture-v3-Full-768x649.png 768w\" sizes=\"auto, (max-width: 796px) 100vw, 796px\" \/><\/a><\/p>\n<p><strong>d. System design description<\/strong><\/p>\n<p>&nbsp;<\/p>\n<p><strong><em>Mechanical System<\/em><\/strong><\/p>\n<p>We are using 3DR X-8+ UAV for our project. The mechanical system of our project consists of the\u00a0propulsion system and the gripper. The propulsion system is part of the 3DR kit that we purchased but\u00a0must be controlled appropriately by our software. The gripper is made by NicaDrone &#8212; an electro-\u00a0permanent magnet. This gripper is the interface between the vehicle and the package and must allow\u00a0the package to be dropped off upon arriving at the destination. It will be controlled by our flight control\u00a0system which is the brain of the UAV.<\/p>\n<p>&nbsp;<\/p>\n<p><strong><em>Electrical System<\/em><\/strong><\/p>\n<p>The electrical system is composed on a high-level by the flight control board, the vision subsystem\u00a0hardware, sensors, and the communications hardware. The flight controller is Pixhawk the brain of the\u00a0entire system and runs all \u00a0critical flight control software. The flight controller interacts with two sensors\u00a0on the vehicle: the IMU and GPS. The flight controllers takes commands from the main processing board\u00a0which directs it to avoid obstacles and land on visual markers. The output from the flight controller goes\u00a0to the motor controller and is then converted into appropriate signals to control the propulsion system.<\/p>\n<p>Odroid &#8211; microprocessor for running visual algorithms connects to the camera and Lidar on board the\u00a0UAV. Odroid runs vision and obstacle detection algorithms and outputs the result to the flight controller.<\/p>\n<p>&nbsp;<\/p>\n<p><strong><em>Software<\/em><\/strong><\/p>\n<p><a href=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-184838.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-494\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-184838.png\" alt=\"Software architecture of the system\" width=\"487\" height=\"213\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-184838.png 487w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-184838-300x131.png 300w\" sizes=\"auto, (max-width: 487px) 100vw, 487px\" \/><\/a><\/p>\n<p>The software of the system comprises of 2 main levels. The lower level control is implemented in the\u00a0flight controller. This runs the control environment to monitor the position and orientation of the UAV to\u00a0maintain stable flight. It uses the GPS, Compass, IMU and a Barometer as sensors.<br \/>\nThe higher level control runs the application specific program and controls the UAV through the lower\u00a0level control. It interfaces with the camera and the Lidar. It runs the behavior program in addition to the\u00a0vision processing algorithms (AprilTag detection), obstacle detection and planning algorithms.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p><a name=\"systemperformance\"><\/a><strong>4. System performance<\/strong><\/p>\n<p>&nbsp;<\/p>\n<p><strong>Fall Validation Performance Evaluation Matrix<\/strong><\/p>\n<table width=\"1157\">\n<tbody>\n<tr>\n<td width=\"289\"><strong>\u00a0Requirement number<\/strong><\/td>\n<td width=\"289\"><strong>Requirement<\/strong><\/td>\n<td width=\"289\"><strong>Subsystem<\/strong><\/td>\n<td width=\"289\"><strong>Performance<\/strong><\/td>\n<\/tr>\n<tr>\n<td width=\"289\">MN3<\/td>\n<td width=\"289\">Detect static obstacle of minimum size<\/p>\n<p>1.5 m X 0.5 m &amp; 2m X 2m<\/td>\n<td width=\"289\">Obstacle detection<\/td>\n<td width=\"289\">Successful within error margin of 20cm<\/td>\n<\/tr>\n<tr>\n<td width=\"289\"><\/td>\n<td width=\"289\">Detect obstacles of minimum size 1.5 m X 0.5 m in natural environment<\/td>\n<td width=\"289\">Obstacle detection<\/td>\n<td width=\"289\">Successful within error margin of 20cm<\/td>\n<\/tr>\n<tr>\n<td width=\"289\">MN4<\/td>\n<td width=\"289\">Marker should be detected in 20cm to 20m range<\/td>\n<td width=\"289\">Vision<\/td>\n<td width=\"289\">Successful<\/td>\n<\/tr>\n<tr>\n<td width=\"289\"><\/td>\n<td width=\"289\">Manual flight control<\/td>\n<td width=\"289\">Flight Control<\/td>\n<td width=\"289\">Successful initially<\/p>\n<p>Later compass problem<\/td>\n<\/tr>\n<tr>\n<td width=\"289\">MF8<\/td>\n<td width=\"289\">Take coordinate as input from user<\/td>\n<td width=\"289\">Flight Control<\/td>\n<td width=\"289\">Successful initially<\/p>\n<p>Later compass problem<\/td>\n<\/tr>\n<tr>\n<td width=\"289\">MF9<\/td>\n<td width=\"289\">Communicate with ground platform to receive GPS updates<\/td>\n<td width=\"289\">Flight Control<\/td>\n<td width=\"289\">Successful initially<\/p>\n<p>Later compass problem<\/td>\n<\/tr>\n<tr>\n<td width=\"289\">MF3<\/td>\n<td width=\"289\">Waypoint Navigation<\/td>\n<td width=\"289\">Flight Control<\/td>\n<td width=\"289\">Successful initially<\/p>\n<p>Later compass problem<\/td>\n<\/tr>\n<tr>\n<td width=\"289\">MN1<\/td>\n<td width=\"289\">Operate in outdoor environment<\/td>\n<td width=\"289\">Obstacle Detection &amp; Vision<\/p>\n<p>Flight Control<\/td>\n<td width=\"289\">Successful<\/p>\n<p>Compass issue<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p><strong>Strengths and weakness of our system &#8211; Fall 2015<\/strong><\/p>\n<p><strong>Strength &#8211; Vision System<\/strong><\/p>\n<p>The vision system has been developed to run using a Logitech webcam on an Odroid. We use nested AprilTag markers and AprilTag detection coupled with Lucas Kanade tracking algorithm to track the marker location. It is able to achieve upto 29 frames per second update rate and can detect the marker upto 20m. To summarize, our vision system looks strong and ready to be integrated. The algorithm used is fast, robust and accurate and based on initial estimates should be able to guide the UAV to land.<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Neutral System &#8211; Obstacle Detection System<\/strong><\/p>\n<p>On the Obstacle Avoidance end, 14 ultrasonic sensors are sufficient to cover area of 1.5 m radius around the UAV. Using serial pining we can get rid of interference. The update rate for the system is around 250 ms which is good. The sensors are not very precise and give around +-20cm error when obstacle are not exactly perpendicular to the sensor. However the error of the system is within the limits of our system requirements.<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Weakness &#8211; UAV\/Flight control<\/strong><\/p>\n<p>We realize that the FireFly6 is the weakest subsystem of our project at this point in time. The UAV is also the most important subsystem of our project and must be made operational as soon as possible. Due to this realization, we are contemplating as part of our risk mitigation to change platforms entirely and go with an octocopter capable of doing everything the FireFly6 does just at slower speeds and with less flight time. Cutting our losses and modifying our project will be the best thing for our project long term and so we believe it is the right move to take at this time.<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Spring\u00a0Validation Performance Evaluation Matrix<\/strong><\/p>\n<p><strong>Package delivery without obstacles<\/strong><\/p>\n<p>A 9.5\u201d x 6.5\u201d x 2.2\u201d package weighing 200g was delivered 30cm from the center of the marker. The UAV\u00a0took off from a starting position around 25m away from the house and landed back on a the truck position\u00a0another 20m away from the house.<\/p>\n<p><a href=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-180800.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-482\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-180800.png\" alt=\"\" width=\"673\" height=\"201\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-180800.png 673w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-180800-300x90.png 300w\" sizes=\"auto, (max-width: 673px) 100vw, 673px\" \/><\/a><\/p>\n<p><strong>Package delivery with obstacles<\/strong><\/p>\n<p>A 9.5\u201d x 6.5\u201d x 2.2\u201d package weighing 200g was delivered 80cm from the center of the marker. The UAV\u00a0took off from a starting position around 12m away from the house and landed back on a the truck position\u00a0another 20m away from the house.<\/p>\n<p><a href=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-181237.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-483\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-181237.png\" alt=\"\" width=\"709\" height=\"276\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-181237.png 709w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-181237-300x117.png 300w\" sizes=\"auto, (max-width: 709px) 100vw, 709px\" \/><\/a><\/p>\n<p><strong>Strengths and weakness of our system &#8211; Spring 2016<\/strong><\/p>\n<p>Overall system performance is strong and robust. Package delivery without obstacles is stable and\u00a0repeatable. Obstacle avoidance has issues related to field of view.<br \/>\nDetailed strengths and weaknesses of the subsystems are listed in table<\/p>\n<p><a href=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-181518.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-484\" src=\"http:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-181518.png\" alt=\"Screenshot from 2016-05-06 18:15:18\" width=\"683\" height=\"237\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-181518.png 683w, https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-content\/uploads\/sites\/2\/2015\/09\/Screenshot-from-2016-05-06-181518-300x104.png 300w\" sizes=\"auto, (max-width: 683px) 100vw, 683px\" \/><\/a><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>1. System summary With a surge in e-commerce logistics, more efficient package delivery mechanisms are required\u00a0to\u00a0deliver more packages in less time at a smaller cost. A hybrid-vehicle autonomous delivery system\u00a0which uses both Autonomous Ground Vehicles and Unmanned Aerial Vehicles can be time efficient\u00a0while maintaining the cost for delivery. The major problem with delivering packages using<br \/><a class=\"moretag\" href=\"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/systems-engineering\/\">+ Read More<\/a><\/p>\n","protected":false},"author":18,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-20","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-json\/wp\/v2\/pages\/20","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-json\/wp\/v2\/users\/18"}],"replies":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-json\/wp\/v2\/comments?post=20"}],"version-history":[{"count":29,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-json\/wp\/v2\/pages\/20\/revisions"}],"predecessor-version":[{"id":346,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-json\/wp\/v2\/pages\/20\/revisions\/346"}],"wp:attachment":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2015teama\/wp-json\/wp\/v2\/media?parent=20"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}