Robot Name: DogBot

Author: Valerie Serluco

Date: December 08, 2015

Instructor(s):

Dr. Arroyo

Dr. Schwartz

TA(s):

Andrew Gray

Jacob Easterling

EEL 5666C

FALL 2015

1 | P a g e

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

• User Search: DogBot will locate through using ultrasonic pulses

• Ball Tracking: Once user is located PlayStation Eye will locate ball

Fetch

• 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

2 | P a g e

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

Infrared Sensor (3x)

Bricktronics MegaShield

NXT Motor (3x)

NXT Touch Sensor

PlayStation Eye

3 | P a g e

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.

4 | P a g e

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.

5 | P a g e

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: 80.179 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: 10 – 80 cm Supply Current: 30 mA

Application

Find road obstacles

6 | P a g e

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.

7 | P a g e

CODE

https://vserluco.wordpress.com/intelligent-machines-design-lab/source-code/