I used the HM-LD1 dToF LiDAR, yep, the robot vacuum sensor, to build an obstacle-stop demo on my drone. it is easy to replicate. l will open-sourcing on GitHub soon.
I mounted the HM-LD1 dToF LiDAR on the front of my drone, enabling it to brake automatically 10 meters before obstacles. Despite its compact size, it gives my drone DJI-level obstacle avoidance, looks good.The code is also open-sourced on GitHub by myrobotproject .
I integrated the HM-LD1 dToF LiDAR with Raspberry Pi 4B, displaying real-time point cloud data on a Waveshare portable screen. Plug-and-play via USB, SDK open-sourced on GitHub: https://github.com/myrobotproject/HM-LD1-OpenCV-Demo Any cool project ideas using dToF? Looking to build something hands-on to level up my skills.Can u drop your suggestions?
I have successfully integrated the HM-LD1 dToF LiDAR with Raspberry Pi, displaying real-time point cloud data on a Waveshare portable screen. If your project requires a compact yet high-precision ranging solution, this significantly streamlines the deployment process. The LiDAR is plug-and-play via USB, and the SDK is open-sourced on GitHub. GitHub link: https://github.com/myrobotproject/HM-LD1-OpenCV-Demo
I built a rear obstacle avoidance system on the LIMO robot using the HM-LD1 dToF LiDAR. Mounted at the rear of the vehicle and powered by a Jetson Nano for real-time data processing, the system enables precise reverse obstacle avoidance — the robot automatically detects rear obstacles and comes to a stable stop before collision. Full source code will be open-sourced on GitHub.
I gave the P100R a try and took a preliminary look at its depth imaging. I'm not entirely sure about its effective measurement range, though. The product documentation claims it can reach up to 8 meters at maximum, which I'll test in my next session. Has anyone else here used it? I also came across someone on GitHub running YOLO object detection with it.
l Picked up the new HM-LD1 dToF LiDAR from myrobotproject recently and decided to test it on a drone I've been working on for an obstacle avoidance project.Low latency, crisp close-range detection, and no issues with weight or power draw on a small airframe.Overall, it performed better than I expected.