A Basic Visual Guidance Sensor Subsystem for Racing Autonomous Robots

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1 A Basic Visual Guidance Sensor Subsystem for Racing Autonomous Robots Progress Report 1 Group #2 Elaine Yan V , Jeremiah Wilbur V , Tiffany Yu V , Ruben du Plessis, V , Faculty Supervisor: Dr. Jim Collins Dr. Adam Zielinski (Co-supervisor)

2 Table of Contents 1.0 Problem Considerations Scope of Project Proposed Solution Assigned Tasks Anticipated Milestones... 3

3 Project Summary This project takes an existing Remote Controlled (RC) car that has been previously modified by a 499 group. This autonomous smart car was built with a Nintendo Wii camera, a microcontroller and infrared distance sensors that allowed it to avoid obstacles in its path, while following a user equipped with two IR light sources set a fixed distance apart. For our project, we will be replacing the Wii camera with a Raspberry Pi camera, the microcontroller with a Raspberry Pi B, and modifying the placement of the IR sensors. The new robot will then use information about its start location and the location of a set of pylons to navigate around the pylons in a pattern. It will be using a three axis accelerometer to maintain an idea of its location until it is in range of the next pylon where it will attempt to correct its location using the camera before rounding the pylon and heading to the next location.

4 1.0 Problem Robots can be used in many capacities. For this project, the robot being built will focus on using image detection to autonomously navigate its way through an obstacle course, marked by brightly colored pylons. The robot used for this project is an Autonomous Smart Car, previously built by a recent 499 group from a Traxxas Slash RC model. Using this model and its existing features, our group will focus on modifying the robot so that it can navigate pre-set track autonomously based only on the image data provided by the camera and knowledge of its starting position. This will require processing the image data to determine the relative location of the pylon to the robot and then generating the appropriate steering control signals. 2.0 Considerations Our group considered two primary options for our robot model before deciding the RC Autonomous Smart Car would work best. The first option was the Romo, built by Romotive. This robot is an iphone dock with rolling tracks, that when connected with an iphone running the Romo app, will turn into an interactive Robot that children can program and play with. Our team looked into how feasible it would be to work with the Romo, including camera feed and data feed features with the Romo SDK, and modifying Romo s mechanical body to add an arm. After talking to one of the Romo developers and Customer Support, it was concluded that using the Romo for our project would only work if we purchased and worked with Apple s SDK. Furthermore modifying the Romo to add an arm or manipulator and then adding the method to 1

5 control this from the iphone would require either having access to the Romo hardware or setting up a complex external control scheme, neither of which will be feasible. Our second option was using the Autonomous Smart Car from a previous 499 group, which has steering and drive as well as possible distance sensors. Our team chose this option because we feel it would be easier to modify since the ROMO has no IO for controlling anything and the ideas we had to get data from all require significant additional hardware to understand what the phone. On the 499 RC car, we plan on replacing the microcontroller and camera with a Raspberry Pi and Pi camera, which we think will have the processing power to detect the pylons. 3.0 Scope of Project The scope of this project is to be able to get the car to effectively navigate the course using the pylons as a location reference. Additionally a possible extra feature would be to use the existing IR sensors to add a more dynamic collision avoidance while still having the robot effectively navigate the track. 4.0 Proposed Solution To enable the car to navigate autonomously will be using a Raspberry Pi B, along with a Pi camera to capture the image data. Using the data we will determine the location of the robot relative to the pylons. Then using the internal map of the course along with the data from the 2

6 accelerometer, the robot will be able to steer itself around the course by sending the correct PWM signals to the steering servo and electronic speed control system for the motor. 5.0 Assigned Tasks Section 5 of the report contains Table 1 of the broken down tasks per week. We will collaborate and communicate with each other to complete each task by the date specified in each row. In general, Elaine will work on assembling the power supply and additional components together, Ruben will deal with the motor interface, Tiffany will implement the accelerometer and control, and Jeremiah will work on the image processing part of the project. 6.0 Anticipated Milestones Please see Table 1 for our distributed tasks per week. 3

7 Table 1: Project Milestone Outline Date Tasks to Complete by Date Jan. 31 PROGRESS REPORT 1, MILESTONE 1 AND WORK LOG 1 DUE o Have tasks listed for Jan. 31 completed Testing PWM control for servo and motor Identification of specific color ranges Feb. 7 Purchase Accelerometer Get materials Raspberry Pi power supply Research which pins to use for the PWM controller, and possibly how to setup how to configure other pins for PWM controller. Internal map of the track Feb. 14 Interface with Accelerometer Generation and transmission of the correct PWM signals Feb. 21 MILESTONE 2 AND WORK LOG 2 DUE o Have all tasks listed up to Feb. 14 completed for Milestone 2 Use accelerometer and initial position to determine location Construct power supply (battery) Note: Progress Presentation (5 mins) on Feb. 25, Mar, 4 or 11, to be assigned) Feb. 28 Coordination of motor servo for correct steering behaviour get pylon materials Mar. 7 PROGRESS REPORT 2, MILESTONE 3 AND WORK LOG 3 DUE o Have all tasks listed up to Feb. 28 completed for Milestone 3 Determining the size and relative position of the pylon based on the location of the pylon in the image data Get mounting materials Get PCB Mar. 14 Use image data to correct current position Mar. 21 MILESTONE 4 AND WORK LOG 4 DUE o Have all tasks listed up to Mar. 14 completed for Milestone 4 Generate proper steering output based on pylon and track location data Mar. 28 DEMO DAY AND DEMO DOCUMENTS Apr. 4 FINAL REPORT, URL, MILESTONE 5 AND WORK LOG 5 DUE 4

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