NDSU team finishes fourth at autonomous vehicle competition

NDSU team finishes fourth at autonomous vehicle competition


A team of five NDSU students placed fourth in the Intelligent Ground Vehicle Competition’s Autonav Challenge, held June 7-10 at Oakland University in Rochester, Michigan.

The NDSU Autonomous Bison Team included students Andrew Jones, Daniel Anderson, Qianqian Yao, Rodi Murad, Avijeet Tomer and Ali Rahim Taleqani. Jones was the team lead.

The vehicle competition, and the Autonav Challenge in particular, are designed to push students to develop technologies that advance autonomous vehicles and robotics. The competition focused on technologies that would be required for on-road and off-road operations of autonomous vehicles.

“It was a challenging competition,” Jones said. “It was a lot of work and provided us with an excellent learning environment. The outdoor environment can be particularly challenging due to rain, mud and sunlight intensity which can affect the robot’s camera and its mobility.”

The 2019 event was the 27th Intelligent Ground Vehicle Competition. The event drew sponsorship and attendance from multiple automotive industry companies that were looking for student talent and technical solutions.

“Robotics competitions allow students to show that they can apply what they’ve learned in and out of the classroom environment,” said Jeremy Straub, assistant professor of computer science, who mentors the team. “They allow students to demonstrate both their technical skills and other critical skills such as teamwork and management. Watching the teams gives employers an opportunity to identify the top prospective talent for their organizations – and to see them in action.”

The NDSU team spent the 2018-2019 academic year working on developing their robot and their design paper submission. Many of the team members also participated in the competition last year. The team’s design is based on a recycled mobility scooter chassis that is augmented with new control hardware and a command system. The vehicle uses both LIDAR and visible light data to sense obstacles and perform route planning.

“I enjoyed working through the many challenges of this project and designing many of the components that were needed for the robot,” said Anderson. “The project tested my knowledge and skills in more ways than just writing code as we worked to finish the bot for the competition. Each component we worked with required its own integration, and the team rose to the challenge. I am proud of what we have accomplished here and it was really exciting seeing it compete.”

The team plans to compete again next year and to further develop their autonomous vehicle to meet changed competition requirements.

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