-
Notifications
You must be signed in to change notification settings - Fork 22
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
What sensors to use on full size SDC? #2
Comments
Three Sensor Types Drive Autonomous Vehicles |
See ideas collected here, about LIDAR simulation: |
Cameras: The Eyes of Autonomous Vehicles |
An Introduction to LIDAR: The Key Self-Driving Car Sensor https://news.voyage.auto/an-introduction-to-lidar-the-key-self-driving-car-sensor-a7e405590cff |
A Coherent Vision for Autonomous Vehicle Sensors |
LiDAR vs. RADAR | Sensors Magazine |
Autonomous Vehicles and Their Sensors https://www.azosensors.com/article.aspx?ArticleID=1250 See also the sources, at the end of the article. |
What sensors do driverless cars have? |
Sensors for autonomous vehicles |
Infrared Sensors for Autonomous Vehicles |
360° Sensors give autonomous cars vision |
Introducing the VoyageG2 Autonomous Vehicle |
Sensors Map the Path to Fully Autonomous Vehicles - Novus Light Today |
RoboSense LIDAR |
The Autoware Foundation Autoware.IO The Autoware Foundation has an impressive list of founding members, including RoboSense, Tier IV, Linaro/96Boards, Apex.AI, ARM, AutoCore, AutonomouStuff, eSOL, Intel Labs, Huawei/HiSilicon, Kalray, LG Electronics, Nagoya University, Open Robotics, Parkopedia, SEMI Japan, SiFive/RISC-V Foundation, StreetDrone, Toyota Research Institute-Advanced Development, Velodyne LiDAR, and Xilinx. |
Check sensors used here: GTC 2018: Learning Steering for Parallel Autonomy. Alexander Amini |
This graphic is pretty good. It explains the design for Tesla Autopilot 2.0 and Mercedes E Class - https://i.redd.it/47ezobni6atx.png Tesla's Autopilot 1: 1 radar, 1 camera, 12 sonar |
One case study with Point Grey cameras - https://www.ptgrey.com/case-study/id/10393 |
From WaveLab SDC team from Waterloo University Canada: Graph SLAM with Clearpath Husky and Velodyne VLP-16s This video shows some results of the Graph SLAM implemented with GTSAM on a point cloud dataset collected using a Clearpath Husky UGV and two Velodyne VLP-16 lidars. |
Contribute ideas, articles, projects that would help select best sensors for different configurations of SDCs.
Best ideas will be integrated in the OSSDC Hacking Book.
We prefer affordable sensors that can be used in open source projects.
Here you can see what kind of sensors we will need:
https://slides.com/mslavescu/self-driving-cars/
The text was updated successfully, but these errors were encountered: