EEL 5666C FALL Robot Name: DogBot. Author: Valerie Serluco. Date: December 08, Instructor(s): Dr. Arroyo. Dr. Schwartz. TA(s): Andrew Gray

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1 EEL 5666C FALL 2015 Robot Name: DogBot Author: Valerie Serluco Date: December 08, 2015 Instructor(s): Dr. Arroyo Dr. Schwartz TA(s): Andrew Gray Jacob Easterling

2 INTRODUCTION ABSTRACT One of the fun things to do when you have a dog is to go outside and play a game of fetch. Unless you re like me that has a dog that doesn t like to fetch. Well in any case, whether your dog is living with your parents or they just don t like to fetch; DogBot is your solution. DogBot will fetch every ball you throw and bring it back no matter where you are. OBJECTIVE DogBot was built to track the ball throughout the process of being thrown to where it lands on the ground using visual input. The visual input will be through PlayStation Eye camera using opencv and python software. Once DogBot picks up the ball, it will use ultrasonic tracking to make its way back to the user to return the ball. This will done through PlayStation Eye camera searching for the base. BEHAVIOR Search Fetch User Search: DogBot will locate through using ultrasonic pulses Ball Tracking: Once user is located PlayStation Eye will locate ball Ball Tracking: PlayStation Eye will track ball being thrown Avoidance: While DogBot is in motion, it will autonomously be looking for obstacles and avoid contact Grab-n-Lift Arm: DogBot's arm will grab and lift the ball up in the when to be transported Return User Search: DogBot will use PlayStation eye to find user's location Grab-n-Lift Arm: DogBot will then place ball at user's feet 1 P a g e

3 INTEGRATED SYSTEM DogBot is using a Raspberry Pi 2 to fulfill the role of a microprocessor. The Raspberry Pi 2 will then control an Arduino Mega 2560, which will act as a slave. Attached to the Arduino Mega is the Bricktronics MegaShield which is the controller for all the LEGO Mindstorms NXT components. The infrared sensors will be connected to the Arduino Mega. The infrared sensors feedback will be used for conditions of the NXT motor controls. The PlayStation Eye which is used to track the ball is connected to the Raspberry Pi 2. The PlayStation eye is mounted on the servo motors allow the robot to have a moveable view. The infrared sensors are used for obstacle avoidance allowing DogBot to maneuver away from walls and objects. Raspberry Pi 2 Servo Motor (2x) Arduino Mega 2560 PlayStation Eye Infrared Sensor (3x) Bricktronics MegaShield NXT Motor (3x) NXT Touch Sensor 2 P a g e

4 DESIGN DIAGRAM The Raspberry Pi 2 and the accessories connected directly to it will handle the higher level thinking. The Arduino Mega is used for the lower thinking of motor control and obstacle avoidance. 3 P a g e

5 MOBILE PLATFORM The DogBot platform will be built using Legos parts from a LEGO Mindstorms NXT kit. I chose to use Legos because it was cost effective due to that I already owned it. I then used the LEGO Digital Designer to sketch a CAD drawing of the platform. I have chosen to use a two wheel drive and having a roller wheel on the back. PLATFORM ARM The DogBot arm will be powered by one NXT motor. The motor will be used to control the motion of clamping the ball as well as raising up the arm. This is done by using a mixture of online and my own designs. The forces on the clamp gears will stall after it grasps the ball and the following gear motion will raise the arm. 4 P a g e

6 ACTUATION LEGO MindStorms NXT motors (3x) Reason for Purchase Cost effective, since I have already owned these motors Motor Specifications Rotation Encoder Returning the position of the shaft with 1 resolution Nominal Voltage: 9 V Nominal Current: 60 ma Free RPM: 170 Stall Torque: 50 N cm Stall Current: 2 A Weight: g MG 995 Servo Motors (2x) Motor Specifications Nominal Voltage: 4.8 V to 7.2 V Stall Torque: 8.5 kgf cm Weight: 55 g SENSOR Analog Distance Sensor (3x) Specification Vendor: Pololu Model: Sharp GP2Y0A21YK0F Range: cm Supply Current: 30 ma Application Find road obstacles 5 P a g e

7 NXT Touch Specifications Unknown Application Used to when the arm is fully lifted PlayStation Eye Specifications Resolution: 640 x 480 Video Frame Rate: 120 FPS Dimensions: 2.56 x 3.15 x 2.17 in Application Used as a special sensor to track the ball being thrown CONCLUSION WORK ACCOMPLISHED In summary of my work, I have successfully built and coordinated a robot to pick up and return a ball to the user. LIMITATIONS At the beginning of this project, I have planned for the robot to find the user by using Ultrasonic sensors. I was not able to reduce the amount of noise feedback when testing in the New Engineering Building Rotunda. So instead I use the PlayStation eye to find the user base. IMPROVEMENTS If I could do this project over again, I would re-design my mobile platform to be for compact and efficient on tracking the ball. 6 P a g e

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