Autonomous Robot for Intelligent Ground Vehicle Competition
Faculty Mentor Name
Douglas Isenberg
Format Preference
Poster
Abstract
IGVC (Intelligent Ground Vehicle Competition) is a nationwide event that offers students an interdisciplinary engineering experience that drives for innovation of mobile autonomous technology. The primary event in this contest pits a robot against grassy terrain marked with faint borders and littered with large obstacles for the machine to independently maneuver around. The primary challenges associated with this event are chassis and software. For simplicity, the robot body will consist of a welded metal frame that maneuvers via differential steering. A full Computer-Aided Design (CAD) model is currently in development, which will allow for detailed simulation and analysis of chassis performance prior to fabrication. On the software side, vision processing and path-planning algorithms will be implemented through OpenCV and Robotic Operating System (ROS) library interfacing, running on a raspberrypi/ Arduino hardware combination. Additionally, the robot is projected to make use of Light Detection And Ranging (LIDAR) sensory, which employs laser imaging techniques for accurate terrain mapping.
- POSTER PRESENTATION
- EAGLE PRIZE AWARD
Location
ERAU - Prescott, AZ; AC1-Atrium, 11 am - 3 pm | Eagle Gym, 7 - 9 pm
Start Date
3-29-2019 11:00 AM
End Date
3-29-2019 9:00 PM
Autonomous Robot for Intelligent Ground Vehicle Competition
ERAU - Prescott, AZ; AC1-Atrium, 11 am - 3 pm | Eagle Gym, 7 - 9 pm
IGVC (Intelligent Ground Vehicle Competition) is a nationwide event that offers students an interdisciplinary engineering experience that drives for innovation of mobile autonomous technology. The primary event in this contest pits a robot against grassy terrain marked with faint borders and littered with large obstacles for the machine to independently maneuver around. The primary challenges associated with this event are chassis and software. For simplicity, the robot body will consist of a welded metal frame that maneuvers via differential steering. A full Computer-Aided Design (CAD) model is currently in development, which will allow for detailed simulation and analysis of chassis performance prior to fabrication. On the software side, vision processing and path-planning algorithms will be implemented through OpenCV and Robotic Operating System (ROS) library interfacing, running on a raspberrypi/ Arduino hardware combination. Additionally, the robot is projected to make use of Light Detection And Ranging (LIDAR) sensory, which employs laser imaging techniques for accurate terrain mapping.
- POSTER PRESENTATION
- EAGLE PRIZE AWARD