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Varshith Solipuram edited this page Oct 29, 2020 · 7 revisions

Auto-Nav


The IGVC competition is centered around building the next generation of off-road, all-weather autonomous vehicles. The idea is to create a vehicle and tech stack that can navigate through an obstacle course to given GPS waypoints without human intervention. The map is not known beforehand, and while there are certain obstacles that are commonly used, theoretically anything can be placed onto the course. The competition is scored in three main areas. First is the design of the robot as presented in the TDP (a written report on the vehicle) that is given to industry experts for judging. Next, the team is scored based on their presentation of the robot, including a Q&A from the judges. Finally, the robot is put to the test by trying to navigate the fastest route on the AutoNav course. If multiple robots complete the course, the winner is the robot that completed it in the fastest time. Otherwise, the robot that navigates the farthest is the winner. In other words, speed is second to safety.

About the Team

We are a small team of engineering students comprising of both undergraduate and graduate level students. We encompass a wide variety of disciplines ranging from Computer Science to Biomedical Engineering, each bringing a unique perspective to our work. We share a common interest in problem solving, particularly solving issues with the aid of robotic systems.

Auto-Nav team at the competition

Robots

1. Veronica (Ground Rover)

Veronica is a second generation fully autonomous ground rover developed by WSU robotics. She is capable of unmanned navigation, obstacle avoidance, mapping, and has a top speed of 5 mph. Her GPS system is capable of localizing within 2.5cm anywhere on the globe. She is currently being developed and is expected to be fully operational by end of 2020.

Veronica

2. Joy (Ground Rover)

Semi-Autonomous ground rover developed for the international ground vehicle competition 2019. Features a visual processing unit and a robust sensor suite. Capable of simultaneous localizing and mapping of both indoor and outdoor environments.

Joy

    • Lane Detection

    • Pothole Detection

    • Barrel Detection

  • Localization

  • Path Planning

  • Recovery Behaviours

Mechanical

Electrical

Testing

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