First Flight: Intel RealSense D435 Depth Camera on Jetson TX2

 

This is part of a series of posts outlining the evolution of my GroundHog hexacopter into a multi-role UAV.  It is based on a Pixhawk flight controller with a Jetson TX2 companion computer.  It has now been fitted with an Intel RealSense D435 depthcam.

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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.

Installation Sequence

• Flash the TX2 with JetPack 3.2
• git clone https://github.com/IntelRealSense/librealsense.git
• cd librealsense
• sudo apt-get update
• modify librealsense/src/image.cpp as per gist above
• sudo apt-get install git cmake
• sudo apt-get install libssl-dev
• sudo apt-get install libusb-1.0-0-dev pkg-config libgtk-3-dev
• sudo apt-get install libglfw3-dev
• sudo apt-get install libudev-dev
• sudo apt-get install cmake-curses-gui
• sudo cp config/99-realsense-libusb.rules /etc/udev/rules.d/
• sudo udevadm control –reload-rules && udevadm trigger
• reboot
• mkdir build && mkdir install
• cd build
• cmake ../ -DBUILD_EXAMPLES=true -DCMAKE_BUILD_TYPE=release -DBUILD_UNIT_TESTS=false
• make -j4
• sudo make install
• Connect D435 to the USB3 port
• Navigate to the tools at usr/local/bin, such as:
  • ./realsense-viewer

Issues

I am getting some warnings of incomplete frames, but it’s not clear if this is due to a power issue on the powered hub or a software configuration.  Despite this, the provided tools seem to work well and demonstrates some of the best depth camera capabilities I have seen (and this is my third depth camera to date).

MAAXX Europe 2018 DroneJam Coding MasterClass

(Nb. All resources for this post can be found on GitHub at https://github.com/mikeisted/maaxxeurope2018)

It’s been a while since my last post.  My research has since moved towards the use of machine learning in UAVs and so my trusty Groundhog now sports a Jetson TX2 instead of a Raspberry Pi and an Intel Realsense depthcam for ‘deep vision’ to match it’s deep learning capabilities.  But I digress… so I’ll blog more on this another time…

This post is about the DroneJam coding masterclass for autonomous UAV ‘newbies’ I ran for this year’s MAAXX Europe autonomous drone competition, held in March at the University of the West of England.