Robots and other complex machines are usually equipped with a wide variety of sensors. Often, when performing tasks such as driving autonomously or collecting data for offline processing, it is useful to synchronize the different sensors. For example, in my work with 3D Machine Learning, I had to collect a dataset consisting of LiDAR pointContinue reading “Synchronizing LiDAR and Camera Data for Offline Processing Using ROS”
Tag Archives: opencv
3D Object Detection with Open3D-ML and PyTorch Backend
In previous articles, I described how I used Open3D-ML to do Semantic Segmentation on the SemanticKITTI dataset and on my own dataset. Now it is time to move to another important aspect of the Perception Stack for Autonomous Vehicles and Robots, which is Object Detection from Point Clouds. Make sure to install Open3D-ML with PyTorchContinue reading “3D Object Detection with Open3D-ML and PyTorch Backend”
Filtering a Point Cloud to Match the Field of View of the Camera
In a previous post, I described why and how I was collecting a Point Clouds dataset. My setup is depicted in the image above, where a 360°, 32-beam LiDAR is placed above a stereo camera. One of the steps mentioned in the article was to crop (or filter) the Point Cloud to only show points approximatelyContinue reading “Filtering a Point Cloud to Match the Field of View of the Camera”
Simplifying Point Cloud Labeling with Contextual Images and Point Cloud Filtering
Annotating point clouds from multi-line 360° LiDAR is exceedingly difficult. Providing context in the form of camera frames and limiting the point cloud to the Field Of View (FOV) of the camera simplifies things. To achieve this, we first had to replace our old, and not so stable LiDAR mount, with a sturdier one capableContinue reading “Simplifying Point Cloud Labeling with Contextual Images and Point Cloud Filtering”
ROS+Oak-D: Turning a depth image into a 2-D laser scan for obstacle avoidance.
When we applied to the #OpenCV Spatial AI Competition #Oak2021, the very first issue we told the organizers we were going to solve using an Oak-D stereo camera was the inability of our robot to avoid obstacles located lower than the range of its 2D lidar. Back then we had no idea how we wereContinue reading “ROS+Oak-D: Turning a depth image into a 2-D laser scan for obstacle avoidance.”
The Robotics division of SHL (SHL Robotics) joins the OpenCV AI Competition #Oak2021
We are pleased to announce that we are officially part of the second phase of the OpenCV AI Competition #Oak2021. Our team joins over 200 team selected worldwide among hundreds of participants. As a price, OpenCV and Luxonis have awarded us a certificate and a free Oak-D camera (to join the 3 others we alreadyContinue reading “The Robotics division of SHL (SHL Robotics) joins the OpenCV AI Competition #Oak2021”
Soul Hackers Labs 