The flashing from the TOF sensor is normal and should not effect VIO. See the documentation troubleshooting VIO, that should help with debugging https://docs.modalai.com/flying-with-vio/#troubleshooting-vio

That is great to hear. Thanks @Alex-Gardner! I will update. I assumed I was on the latest as I had seen I was on factory bundle 1.0.1 and saw on this page: https://docs.modalai.com/downloads/ That the latest factory bundle was 1.0.1. [image: 1635187077739-32eb6578-ebff-4d43-b1ae-d2dc43d70f7e-image.png] Should I be paying attention to the system-image: ModalAI 3.2.0 When checking whether the system needs an update?

@relevinsky Docker has some pretty good documentation. Have you looked at: https://docs.docker.com/engine/reference/run/#network-settings?

Have you followed the tutorial at https://docs.modalai.com/mavros ?

Hi @Jonathan-Jeff , Theoretically yes but there are limitations. Here's some information that might help in showing some possible options: https://docs.modalai.com/image-sensors/

I didn't know Docker had this feature, so thanks for that tip! Docker built on VOXL is running at version 1.9.0 and from some articles I read it looks like multistage build started in 17.06 (https://docs.docker.com/engine/release-notes/prior-releases/) So I don't believe this is supported.

Thank You for Your responses. Unfortunately Mission Planner doesn't see the device. I also tried via nuttx-shell, but voxl doesn't get any response from stm32, so it's probably a problem with the hardware.

No problem at all, I'll get our docs updated so it's more clear, definitely not a rookie mistake, we should call it out!

@Cool-Karp , Congrats on your success! We are all here to learn so if you have any features you find missing that you found on another development platform please let us know! Thanks

@blakekrpec As I understand the ECL/EKF library integration so far, you can run several instances that each will fuse different sensor combinations (with individual blending) to accommodate for estimation state errors and the like....

Have you followed the mavros tutorial here?

Hello, they are M1.6 x 6mm.

@Prasad-Antervedi Try following these: https://docs.modalai.com/calibrate-cameras/

Camera server has auto-exposure enabled by default on all the cameras, you can verify this by looking at /etc/modalai/voxl-camera-server.conf and by running voxl-inspect-cam hires_preview and shading the lens with your hand, watching the exposure go up and down.

@Alex-Gardner Worked, thanks!

Not modalai, but something that helped me debug this very same issue was installing voxl-portal, and using that to view the qvio stream, which will overlay the points onto the tracking camera screen. If it creates points at your drone's motors and feet, then I presume it would be a problem

Found the repository that stores the code here https://gitlab.com/voxl-public/old-projects/voxl-hal3-tof-cam-ros. If this link could be placed in the documentation for future viewers, that would be great

Thanks for printing out those resolutions. Very helpful! yocto:~$ voxl-camera-server -d 1 exising instance of voxl-camera-server found, attempting to stop it ------ voxl-camera-server INFO: Port J2 ------ voxl-camera-server: Done configuring hires camera Port : port_J2 Name : hires Enabled : 1 Type : hires Api : hal3 P-W : 640 P-H : 480 P-Fmt : nv21 FPS : 30 OverrideId : -1 AEAlgo : isp ------ voxl-camera-server INFO: Port J3 ------ voxl-camera-server: Done configuring stereo camera Port : port_J3 Name : stereo Enabled : 1 Type : stereo Api : hal3 P-W : 1280 P-H : 480 P-Fmt : nv21 FPS : 30 OverrideId : -1 AEAlgo : modalai =================MODALAI Auto Exposure Settings================== gain_min: 0 gain_max: 1000 exposure_min_us: 100 exposure_max_us: 33000 desired_msv: 58.000000 k_p_ns: 32000.000000 k_i_ns: 20.000000 max_i: 250.000000 p_good_thresh: 3 exposure_period: 1 gain_period: 2 display_debug: no exposure_offset_for_gain_calc: 8000 ================================================================= ------ voxl-camera-server INFO: Port J4 ------ voxl-camera-server: Done configuring tracking camera Port : port_J4 Name : tracking Enabled : 1 Type : tracking Api : hal3 P-W : 640 P-H : 480 P-Fmt : raw8 FPS : 30 OverrideId : -1 AEAlgo : modalai =================MODALAI Auto Exposure Settings================== gain_min: 0 gain_max: 1000 exposure_min_us: 100 exposure_max_us: 33000 desired_msv: 58.000000 k_p_ns: 32000.000000 k_i_ns: 20.000000 max_i: 250.000000 p_good_thresh: 3 exposure_period: 1 gain_period: 2 display_debug: no exposure_offset_for_gain_calc: 8000 ================================================================= Writing new configuration to /etc/modalai/voxl-camera-server.conf Created pipe: hires_preview channel: 0 Created pipe: stereo channel: 1 Created pipe: tracking channel: 2 Starting Camera: tracking SUCCESS: Camera module opened ----------- Number of cameras: 3 ------ voxl-camera-server INFO: Client: qvio-server0 connected to channel: 2 ------ voxl-camera-server ERROR: Client connected to invalid channel: 0 ------ voxl-camera-server ERROR: Client connected to invalid channel: 1 ----------- HiRes camera id: 0 ----------- Stereo camera id: 2 ----------- Mono camera id: 1 ------ voxl-camera-server INFO: Client: voxl-streamer0 connected to channel: 2 Available resolutions for camera: tracking: 640 x 480 320 x 240 Resolution: 640 x 480 Found! ------ voxl-camera-server: Preview buffer allocations Internal Exposure for: tracking 2 /builds/voxl-public/modal-pipe-architecture/voxl-camera-server/src/expgain_interface/expgain_interface_factory.cpp 45 Creating exposure interface Creating ModalAI exposure interface Port : port_J4 Name : tracking Enabled : 1 Type : tracking Api : hal3 P-W : 640 P-H : 480 P-Fmt : raw8 FPS : 30 OverrideId : -1 AEAlgo : modalai =================MODALAI Auto Exposure Settings================== gain_min: 0 gain_max: 1000 exposure_min_us: 100 exposure_max_us: 33000 desired_msv: 58.000000 k_p_ns: 32000.000000 k_i_ns: 20.000000 max_i: 250.000000 p_good_thresh: 3 exposure_period: 1 gain_period: 2 display_debug: no exposure_offset_for_gain_calc: 8000 ================================================================= Starting Camera: hires Available resolutions for camera: hires: 4160 x 3120 4056 x 3040 4000 x 3000 3040 x 3040 3016 x 3016 3840 x 2160 3648 x 2736 3264 x 2448 3200 x 2400 2976 x 2976 3044 x 1720 2704 x 2028 2704 x 1520 2592 x 1944 2688 x 1512 2028 x 1144 2160 x 2160 1920 x 2160 1920 x 1920 1880 x 1880 2048 x 1536 1920 x 1440 1920 x 1080 1600 x 1600 1600 x 1200 1520 x 1520 1440 x 1080 1080 x 1080 1280 x 960 1340 x 760 1280 x 768 1280 x 720 1200 x 1200 1280 x 640 1280 x 480 1040 x 780 1024 x 768 960 x 960 720 x 720 800 x 600 960 x 720 848 x 480 858 x 480 864 x 480 800 x 480 720 x 480 640 x 480 640 x 240 640 x 360 480 x 640 480 x 480 480 x 360 480 x 320 432 x 240 352 x 288 320 x 240 Resolution: 640 x 480 Found! ------ voxl-camera-server: Preview buffer allocations Port : port_J2 Name : hires Enabled : 1 Type : hires Api : hal3 P-W : 640 P-H : 480 P-Fmt : nv21 FPS : 30 OverrideId : -1 AEAlgo : isp Starting Camera: stereo Available resolutions for camera: stereo: 1280 x 480 848 x 480 858 x 480 864 x 480 800 x 480 720 x 480 640 x 480 640 x 240 640 x 360 480 x 480 480 x 360 480 x 320 432 x 240 352 x 288 320 x 240 Resolution: 1280 x 480 Found! ------ voxl-camera-server: Preview buffer allocations Internal Exposure for: stereo 1 /builds/voxl-public/modal-pipe-architecture/voxl-camera-server/src/expgain_interface/expgain_interface_factory.cpp 45 Creating exposure interface Creating ModalAI exposure interface Received raw10 frame, checking to see if is actually raw8 Frame was actually 8 bit, sending as is Port : port_J3 Name : stereo Enabled : 1 Type : stereo Api : hal3 P-W : 1280 P-H : 480 P-Fmt : nv21 FPS : 30 OverrideId : -1 AEAlgo : modalai =================MODALAI Auto Exposure Settings================== gain_min: 0 gain_max: 1000 exposure_min_us: 100 exposure_max_us: 33000 desired_msv: 58.000000 k_p_ns: 32000.000000 k_i_ns: 20.000000 max_i: 250.000000 p_good_thresh: 3 exposure_period: 1 gain_period: 2 display_debug: no exposure_offset_for_gain_calc: 8000 ================================================================= ------ voxl-camera-server: Camera server is now running

@colerose we selected mobilenetv2 because of its exceptional performance on embedded devices - currently, inference time in the voxl-tflite-server is ~22ms per frame with very high precision. Also, the mobilenet family is fairly easy to retrain with a custom dataset!