Nvidia Jetson

Algorithms
https://devblogs.nvidia.com/jetson-nano-ai-computing/

https://developer.nvidia.com/embedded/jetson-nano-developer-kit Jetson nano for $100

realsense
https://diydrones.com/profiles/blogs/installing-the-intel-realsense-d435-depth-camera-on-a-jetson-tx2

https://mikeisted.wordpress.com/2018/04/09/intel-realsense-d435-on-jetson-tx2/ Here’s a quick technical post for anyone attempting to harness the capabilities of a Realsense D435 camera on a Jetson TX2. For me, this is about getting usable depth perception on a UAV, but it has proved more problematic than I originally anticipated.

This post aims to provide some simple instructions that now work for me, but took a long time to find out!

The Problem The Intel librealsense2 library does not support ARM architectures as I write. This causes a fatal compile error when the file librealsense/src/image.cpp is accessed, as it queries the system architecture.

Solution Modify image.cpp as in my Github gist here. This bypasses the architecture check.

https://github.com/IntelRealSense/librealsense

https://www.youtube.com/watch?v=5tY2A-_VBi8

uav
https://diydrones.com/profiles/blogs/pixhawk-2-with-jetson-tx2-build

https://mikeisted.wordpress.com/2018/08/23/pixhawk-2-with-jetson-tx2-build/

http://www.jetsonhacks.com/ 192 CUDA core Kepler GPU (APU, accelerated processing unit combines cpu/gpu)

http://www.linuxfromscratch.org/blfs/view/svn/general/opencv.html

http://www.jetsonhacks.com/2015/05/25/quadcopter-control-using-image-recognition-on-jetson-tk1/?relatedposts_hit=1&relatedposts_origin=222&relatedposts_position=1

http://connecttech.com/product-category/form-factors/nvidia-jetson-tx2-tx1/

links
Uav forest trail navigation

Px4

GPU