System Integration and Intelligence
1 / 1

Abstract - PowerPoint PPT Presentation

  • Uploaded on

System Integration and Intelligence Improvements for WPI’s UGV - Prometheus Craig DeMello (RBE), Eric Fitting (RBE/CS), Sam King (RBE), Greg McConnell (RBE), Mike Rodriguez (RBE) Advisors: Professor Taskin Padir (ECE/RBE ) and Professor William Michalson (ECE/RBE ). Abstract

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about ' Abstract' - jam

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

System Integration and Intelligence Improvements

for WPI’s UGV - Prometheus

Craig DeMello (RBE), Eric Fitting (RBE/CS), Sam King (RBE),

Greg McConnell (RBE), Mike Rodriguez (RBE)

Advisors: Professor Taskin Padir (ECE/RBE) and Professor William Michalson (ECE/RBE)


This project focuses on realizing a series of operational improvements for WPI’s unmanned ground vehicle Prometheus with the end goal of a winning entry to the Intelligent Ground Vehicle Challenge. Improvements include a practical implementation of stereo vision on an NVIDIA GPU, a more reliable implementation of line detection, a better approach to mapping and path planning, and a modified system architecture realized by an easier to work with GPIO. The end result of these improvements is Prometheus has improved autonomy, robustness, reliability, and usability.

  • Control Architecture

  • Goals:

  • Exchange cRIO for Arduino

  • Move peripherals to computer

  • Benefits:

  • More robust system

  • Drastically reduced programming time

Path Planning

  • Using its sensory information, Prometheus can intelligently plan paths.

  • The red outline is the robot footprint

  • The blue line is the path from the current position to the goal

  • The red line is the short term path based on the blue line and tentacles

Figure 10: Robot path planning


Figure 4: 2011 Architecture

Figure 5: 2012 Architecture

  • Prometheus’s Extended Kalman Filter:

  • Integrates GPS, Wheel Encoders and Compass

  • Reduces error from sensor drift

  • Provides an accurate estimate of absolute position and heading


Prometheus is an ongoing project at WPI, with the project goal centered around developing a robot capable of being competitive at the international Intelligent Ground Vehicle Competition.




Obstacle Detection

Figure 11: EKF Results

Stereo Vision

Promethus can detect obstacles using it’s two cameras and stereo vision

The shade of grey determines the distance to the item in view

Figure 12: Right stereo camera

Figure 3: 2012 robot

Figure 2: 2011 robot

Figure 1: 2010 robot

  • Use 5% of pre existing code

  • Stereo vision

  • EKF

  • Wheel Encoders added

  • Motors and Compass to main computer

  • Peripherals to Arduino

  • Mechanical Construction

  • Tentacles Implemented

  • Did not qualify

  • Rookie of the year award

  • ROS Implemented

  • Dual cameras and DGPS boom mounted

  • DGPS and Lidar moved to main computer

  • Qualified, 13th place in navigation challenge

Figure 6: Robot point of view

Figure 7: Virtual map

  • The world as Prometheus sees it using its SICK Lidar

  • The green outline represents the robot footprint

  • The red grid cells represent obstacles

  • The yellow cells represent virtual inflation, to keep the robot a safe distance from obstacles.

Figure 14: Stereo vision disparity map

Figure 13: Left stereo camera

  • Accomplishments

  • Robust modular system

  • Competitive performance

  • Implementation of new features over last year

  • Recommendations:

  • Smaller, differential drive platform

Line Detection

Prometheus has the capability to determine the existence and location of lines it cannot cross by:

Morphing the image from the camera into a birds eye view

Blurring the image

Filter out the lines using a Hue Saturation Value filter and pre determined values

Running a Hue lines algorithm

Figure 8: Robot view of line

  • Goals

  • Develop a robot capable of being competitive in the national IGVC competition with the ability to:

  • Autonomously navigate to GPS waypoints

  • Avoid all obstacles

  • Avoid crossing any painted white lines

  • Navigate around flags based on their color



2010 MQP Report: Design and Realization of an Intelligent Ground Vehicle

2011 MQP Report: Realization of Performance Advancements for WPI’s UGV – Prometheus

Figure 9: Line in virtual map