Software for LOCO, our autonomous drifting RC car. See our wiki for details about this repo, and learn more about our project at: http://mrsdprojects.ri.cmu.edu/2016teamd/
Project Video:
Autonomous vehicles are currently being tested and deployed in major cities around the world, and it is not difficult to imagine that they will be fully deployed on public roads within the next 5-10 years. While these vehicles have advanced sensing capabilities and intelligent systems for decision-making and control, they might still be susceptible to external threats on the road, including reckless human rivers and suddenly-appearing wildlife.
We propose a system that can plan evasive maneuvers through extreme situations such as drifting for autonomous vehicles to counteract these threats. Our system capitalizes on the exceptional sensing and computational capabilities of autonomous vehicles to accurately identify and track any sudden or dynamic obstacles, and at the same time plan and generate trajectories for the vehicle to evade these obstacles. We demonstrate that our system is able to perform these maneuvers in a swift and precise manner that is unattainable by typical autonomous driving systems or human drivers.
In this project, we implemented this system on a 1/10 scale RC car with on-board sensors and computation. In our final evaluation, we demonstrated that our robot could avoid a suddenly-appearing obstacle 1.5m away while travelling at 3m/s - a maneuver that is impossible to pull off by automatic braking or human operation.