Real-time Embedded Deep Learning for Autonomous Lane Change Systems of Autonomous Driving
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Updated
Jan 7, 2018 - Python
Real-time Embedded Deep Learning for Autonomous Lane Change Systems of Autonomous Driving
An autonomous intelligent robotic delivery system
Exploiting NVIDIA TX2 Resources for Human Identification with Smart Insoles and OpenPose.
Development of a high-speed (25km/h) 1/10 scale autonomous electric mobile robot using the Nvidia Jetson, Intel Realsense and Hokuyo Lidar
Building the perception stage of a small autonomous racecar system running on NVIDIA Jetson TX2. ZED Stereo Camera is used for visual input. The algorithm is developed in Python 2 using Robot Operating System (ROS). It uses YOLO to extract the detected objects in the racecar's environment and their estimated distances obtained from the stereo ca…
This repository contains the code to control all the traxxis rc cars in a 1/10 scale testbed. Code can be run in simulation or using real vehicles.
DLARM: Dissertation for Computer Science Masters Degree at UFRGS
Tool to run tegrastats and parse the obtained log file to extract useful data into a csv. It also allows for automated graph creation between values desired from the data parsed.
a global localization system with object detection in semantic map
EVDodgeNet: Deep Dynamic Obstacle Dodging with event cameras
Social Distancing Detector using deep learning and capable to run on edge AI devices such as NVIDIA Jetson, Google Coral, and more.
Simple moving graph of GPU activity for the Jetson TX1 and Jetson TX2
This is the implementation of GGHL (A General Gaussian Heatmap Label Assignment for Arbitrary-Oriented Object Detection)
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