A self-driving system developed with Linux & ROS on an NVIDIA Jetson TX2, to demonstrate dynamic inductive charging from the road. The sensor package consists of a lidar and camera. Hector SLAM is used for mapping and localization. Pure Pursuit is used to follow a manually recorded path. Machine-learning and behavior cloning is used to make the vehicle drive with camera only. Recorded camera images and steering input were used as training data to a deep neural network. The truck is controlled with PWM-signals from a Teensy 3.2 microcontroller. There are four different driving modes; manual, record new path, lidar/SLAM-mode, and AI-mode. The truck has an onboard induction charger system that talks with the TX2 through CAN-bus. There is also a custom GUI to monitor the states of the truck and battery.
Link to paper: ntnuopen.ntnu.no/ntnu-xmlui/h...
Github: github.com/joneivind/Self-Dri...
Master Thesis in Cybernetics & Robotics by Jon Eivind Stranden at the Norwegian University of Science and Technology (NTNU) in cooperation with SINTEF Energy Research, 2019.
Music:
Lensko - Let's go
Негізгі бет Ғылым және технология Autonomous RC Truck with Wireless Charging (ROS/Jetson TX2)
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