Hi everyone,

I am using a voxl2 that I received with voxl-suite 0.9.5. Since I wanted to switch voxl-vision-hub I picked the staging pkg manager with the command voxl-configure-pkg-manager and ran apt update.
What I ended up having is the following voxl-version.

voxl2:/$ voxl-version 
--------------------------------------------------------------------------------
system-image: 1.4.1-M0054-14.1a-perf
kernel:       #1 SMP PREEMPT Thu Oct 13 17:48:16 UTC 2022 4.19.125
--------------------------------------------------------------------------------
hw version:   M0054
--------------------------------------------------------------------------------
voxl-suite:   
--------------------------------------------------------------------------------
Packages:
Repo:  http://voxl-packages.modalai.com/ qrb5165 staging
Last Updated: 2023-05-30 15:13:45
List:
   libmodal-cv            0.3.1
   libmodal-exposure      0.0.8
   libmodal-journal       0.2.2
   libmodal-json          0.4.3
   libmodal-pipe          2.8.4
   libqrb5165-io          0.2.0
   libvoxl-cci-direct     0.1.5
   libvoxl-cutils         0.1.1
   mv-voxl                0.1-r0
   qrb5165-bind           0.1-r0
   qrb5165-dfs-server     0.1.0
   qrb5165-imu-server     0.6.0
   qrb5165-slpi-test-sig  01-r0
   qrb5165-system-tweaks  0.1.7
   qrb5165-tflite         2.8.0-2
   voxl-camera-server     1.5.4
   voxl-ceres-solver      1.14.0-9
   voxl-cpu-monitor       0.4.5
   voxl-eigen3            3.4.0
   voxl-jpeg-turbo        2.1.3-4
   voxl-mapper            0.1.9
   voxl-mavlink-server    1.0.5
   voxl-modem             1.0.4
   voxl-mongoose          7.7.0-1
   voxl-mpa-to-ros        0.3.6
   voxl-mpa-tools         1.0.1
   voxl-nlopt             2.5.0-4
   voxl-opencv            4.5.5-1
   voxl-portal            0.5.8
   voxl-qvio-server       0.9.2
   voxl-streamer          0.6.1
   voxl-tag-detector      0.0.4
   voxl-tflite-server     0.3.1
   voxl-utils             1.3.0
   voxl-vision-hub        1.6.5
   voxl-voxblox           1.1.3
   voxl2-system-image     1.4.1-r0
   voxl2-wlan             1.0-r0
--------------------------------------------------------------------------------

At this point, I wanted to switch camera config therefore I ran voxl-configure-cameras 6 (i.e. TOF+Hires+Tracking) but the following error came out:

[ERROR] Your system image is too old to support the new camera driver structure
[ERROR] Plese update to a system image newer than May 14 2023

The weird thing is that this happen with all the other config IDs. However if I unplug the TOF camera sensor I am able to use Hires+Tracking but I still can't switch to any other config ID.

@tom nevermind I found out the documentation here, and by reflashing the platform everything worked again! Thank you for the support!

Is it possible to use 2 tofs + stereo + tracking + hires?

Hi everyone,
I have the following questions regarding the reference frames present in extrinsics.conf file:

• It is my understanding that the body frame is a NED frame located in the geometric center (or center of gravity?) of the drone, but where is the origin along the z axis? Is it considered to be at the center of gravity of the drone?
• Is the ground frame still a NED frame? Where it should be located with respect to the body frame?

Thank you in advance for your response!

To conclude this post in the hope to help someone else who's having the same problem, I found this reply on another question in this forum which dates back to 2021. I guess the Relocalization still works only in Offboard and NOT in Mission. The same applies for an external flight controller e.g. in Ardupilot it works in Guided Mode and NOT in Auto.

@Moderator thank you for the reply, by board I meant the checkboard used for the calibration not the PCB.

However, I watched the video, but it looks old because the current extrinsics procedure is asking me to move the checkboard in 4 poses whereas the video is showing only 2 poses. How much tilt should the checkboard have during the extrinsics calibration process in order to have a low calibration error?

Hi everyone,

I am trying to calibrate the hires camera after I put the image in focus (see image below), using the following command:

voxl-calibrate-camera hires -s 5x7 -l 0.0655

I keep getting re-projection error around 15, but it's very hard to understand why. I tried 2 different checkboards of different sizes but I am keep having the same error. Do you have any insights on what might be the issue?

@modaltb Thanks, despite the delay, for the response! I only have one last question in this regard: is it possible to rotate the stereo ov7251 by 90 degrees or currently it is only possible to flip them by 180?
This info would help me a lot. Thanks!

@thomas Thanks a lot for the support! I'll dig into it and go back to you in case something is not clear!

@thomas Thank you for your response! That would be great, could you please show me a bit more precisely where can I start to edit the code to make this adjustments?

@Moderator thank you for your response!
I agree with what you suggest, but we are not discussing about the computation of the disparity in an edge case scenario of a white wall. I am just confused, for instance take the example below: why the voxl-disparity is so sparse (first top picture) with respect to the other done via opencv (second bottom picture)?

top-disparity

bottom-disparity

In both cases I am using the same grey images, with the same extrinsics/intrinsics parameters, and yet the disparity from opencv is able to fill in the areas within the edges, whereas voxl-disparity is not. Are there any parameters that I can tune to get the top-disparity to look more similar to the bottom-disparity?

@thomas Sure, the model that I am using is the D455.

I was just trying to understand if the disparity that I am getting from voxl-dfs-server (now) is the best that I can get (or at least not too far from the best that I can get). This is why I asked if you could post a good disparity taken with one of your stereo setup. The one in the website https://docs.modalai.com/voxl-dfs-server-0_9/ looks very similar to what I am getting ATM: good disparity along the edges of the objects, but no information in uniform areas.

Thanks again for the reply!

@thomas Thank you for your response, On the SDK 0.9 I have the same issue. I tried to re-focus the cameras and re-calibrate them and the dfs has improved maybe slightly:
no parameter tuning

post_median_filter=15

post_median_filter=15, blur_filter=5

post_median_filter=15, blur_filter=5, dfs_pair_0_cost_threshold=80

However, I am not able to get a uniform disparity as the one that I would get from the intel sensor for example, there are always a lot of holes over the objects in the scenes.

Is there a way to fine tune this? Maybe a parameter in voxl-dfs-server that I did not yet tweaked?
Could this be related to other macroscopic issues?

Thank you in advance for your response!

Hi everyone,

I am using a Sentinel (1) drone upgraded to the SDK 1.1.0. I was trying to get the disparity out of the frontal stereo however the results are quite bad, please see below the output of the sentinel (greyscale) vs the output of a an intel realsense (colored). For reference the object in view is a library.

I tried to play around with the parameters in voxl-dfs-server, but I can't get a decent result.

1. Do you have any suggestions? I have a feeling that it might be something macroscopic like: camera mounting, stereo out of focus or bad calibration (although I repeated it quite a lot).
2. Could you please post a good disparity taken with one of your stereo setup along with the respective grey scale stereo images? This would help to have a benchmark that I can compare with?

Thank you in advance for your response.

@Alex-Kushleyev Thank you very much for the precise response!!!! I noticed that logDepthBootstrap is harcoded in voxl-qvio-server/server/main.cpp to be log(1) (i.e. 0) here: https://gitlab.com/voxl-public/voxl-sdk/services/voxl-qvio-server/-/blob/master/server/main.cpp?ref_type=heads#L360
but I will try to add it to the qvio server params so that I can tune it more easily.

useLogCameraHeight set to false should enable logDepthBootstrap instead of logCameraHeightBootstrap right? Regarding these two "bootstraps":

1. Could you please explain what is the difference between the two and when should one be preferred with respect to the other?
2. From the comments in https://developer.qualcomm.com/sites/default/files/docs/machine-vision-sdk/api/v1.2.13/group__mvvislam.html#ga6f8af5b410006a44dbcf59f7bc6a6b38 it is not clear to me what the meaning of these two params is: are they expected to work only during the initialization phase? What influence would they have during the rest of the flight?

Thanks again in adavance for your reply.

Hi everyone,

I am using a Sentinel drone upgraded to the SDK 1.1.0 to perform indoor autonomous missions.

The vibrations are all green with voxl-inspect-vibration;
The number of features >10;
Illumination conditions are good: the indoor environment is artificially illuminated with artificial light that don't cause any flickering;
I tried also to use another tracking cam pitched by 15 degrees instead of 45, but the following results are the same

However, I experienced drifts of 3m with respect to the ground truth over 10m of flight. In this case the features were roughly 10-15m away from the drone. Whereas as soon as the features were 30ish m away from the drone, it started to oscillate around the point sent by the mission with an amplitude ~0.5m. Consider the indoor environment as a room where most of the features are concentrated in only one side of the walls.

1)Is this behavior expected by the current VIO? If not, what solutions do you propose?
2) What drift should I expect over 10m in good environment conditions?
3) Slightly unrelated question: Is it possible to use the tracking cam and stereo_rear cam at the same time as input to the qvio-server?

Thank you in advance for your response.

@Alex-Kushleyev Thank you for the help! Can I locate the pgm file anywhere I want on the Voxl2 and specify the absolute path to the pgm in staticMaskFileName or do I have to put the file in a specific path in order for the mvSLAMinitialize function to find it?

Moreover, are there any parameters that can be tweaked to force the qvio to maximize the amount of features across the whole image? When yawing I noticed that the algorithm tends to stick to the features detected in the previous frames rather than picking new ones. As a result, the at the end of the yaw the drone has 20ish features on one side of the image and none on the other side (despite the same lighting conditions) and as a result the quality of the vio can drop below 10% quite easily. Basically I would like the algorithm to switch earlier on new feature candidates rather than keeping old ones in the buffer.