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”