@dlee ,

Yes the new TOF sensor (IRS2975C) is more powerful that the previous generation. What I mean by that is that it can emit more IR power but also heats up more. Emitting more power allows the sensor detect objects at larger distances or objects that are not as reflective.

In current operating mode, the auto exposure control is enabled inside the sensor itself, which modulates the emitted IR power based on the returns that the sensor is getting. That is to say, the power draw will vary depending on what is in the view of the sensor. If there are obstacles nearby, the output power should be low, otherwise it can be high. At full power, the module can consume close to 0.8-0.9W

So the first solution, if design allows, is to add a heat spreader to dissipate the heat, which you already started experimenting with. The sensor has a large exposed copper pad in the back for heat sinking purposes for this exact reason. Just be careful not to short this pad to anything, use non-conducting (but heat transfering) adhesive pad between the sensor and heat spreader.

In terms of a software solution to the issue, we can query the temperature of the emitter. We can also control the maximum emitted power used by the auto exposure algorithm. That is to say, still leave the auto exposure running in the sensor, but limit the maximum power that it is allowed to use.

We are planning to add some software protection that limits the maximum output power as a function of the emitter temperature. This will require some implementation and testing.

Meanwhile, please consider using a heat spreader, which will be the best solution if you want to make use of the full sensor's operating range and not have our software limit the output power in order to prevent overheating.

Hello @Kashish-Garg-0

we have a curve that is "motor voltage vs rpm", meaning that for a desired RPM, it tells the ESC what average motor voltage should be applied. The average motor voltage is defined as battery_voltage * motor_pmw_duty_cycle. The battery voltage in this curve is in millivolts. Since you are typically controlling the desired RPM, as a user you do not need to worry about what "throttle" or voltage to apply - the ESC does this automatically in order to achieve the desired RPM. this calibration curve is used as a feed-forward term in the RPM controller. The ESC does support an "open loop" type of control where you specify the power from 0 to 100%, which is similar to a standard ESC, but PX4 does not use that ESC control mode.

By the way, you can test the ESC directly (not using PX4) using our voxl-esc tools (https://gitlab.com/voxl-public/voxl-sdk/utilities/voxl-esc/-/tree/master/voxl-esc-tools) which works directly on VOXL2 or a standalone linux PC (or mac). voxl-esc-spin.py has a --power argument where you specify the power from 0 to 100, which translates directly to the average duty cycle applied to the motor.

Here is the calibration for the Starling V2 motor / propeller that we use:
https://gitlab.com/voxl-public/voxl-sdk/utilities/voxl-esc/-/blob/master/voxl-esc-params/mavic_mini_2/mavic_mini_2.xml?ref_type=heads#L63

Also, you can take a look at this post to see how to interpret those parameters a0, a1, a2 : https://forum.modalai.com/topic/2522/esc-calibration/2

We also have some dyno tests for this motor / propeller : https://gitlab.com/voxl-public/flight-core-px4/dyno_data/-/blob/master/data/mavic_mini2_timing_test/mavic_mini2_modal_esc_pusher_7.4V_timing0.csv . We are not sure how accurate that is, but it can be used as a starting point. @James-Strawson can you please confirm that is the correct dyno data for the Starling V2 motors?

Alex

@reber34 , perhaps this approach can work for you:

• record a video encoded at high bit rate (using voxl-camera-server and voxl-record-video . Please note that the output of voxl-record-video will not be in a standard container (such as mp4, etc), but you can fix it with ffpeg : ffmpeg -r 30 -i voxl-record-video.h264 -codec copy videofile.mp4
• re-encode the video offline with desired codecs / bit rates / resolutions
• install gst-rtsp-launch which uses gstreamer to set up an RTSP stream https://github.com/sfalexrog/gst-rtsp-launch/
  • you will first need to figure out what gstreamer pipeline to use on voxl2 that will load your video and parse the h264/h265 frames (can use null sink for testing) and then use that pipeline with gst-rtsp-launch which will take the encoded frames and serve them over rtsp stream.
• gstreamer may be more flexible for tuning the encoding parameters of h264/h265 (compared to voxl-camera-server) and you can also use it in real time later (using voxl-streamer, which uses gstreamer under the hood)

Another alternative is to use voxl-record-raw-image to save raw YUVs coming from voxl-camera-server and then use voxl-replay and voxl-streamer - the latter will accept YUVs from the MPA pipe and encode them using the bit rate that you want. Note that depending on the image resolution, YUV images will take a lot more space than encoded video, but maybe that is also OK since VOXL2 has lots of storage.

Alex

@jimbow77 and @oasisartisan ,

TOF V1 (which is now EOL, so you don't have it on Starling 2 Max) was set up the following way:

• The calibration data was downloaded the first time the sensor was used and stored in /data/misc/camera/, then re-used for next time
• calibration files include pmd.spc, tof_cal_eeprom.bin and irs10x0c_lens.cal - the latter likely containing the intrinsics calibraiton data (although i have not checked explicitly)

TOF V2 (what is shipping in Starling 2 (and Max) ), is set up so that the TOF Library downloads (via i2c) the calibration data each time the voxl-camera-server starts. This is done internally to the TOF libraries. I don't know exactly why there is a difference between how the calib data is handled for two sensors by the TOF software, but this is how our sensor vendor helped us set it up. The TOF processing software downloads the calibration from the sensor each time voxl-camera-server starts and applies it to generate the point cloud. It may be possible to get the TOF intrinsics using the TOF library API, but we have not checked.

Do you have a specific reason why the TOF intrinsics are needed?

If you wanted to calibrate the TOF sensor yourself, then you would either need a checkerboard some material that is IR reflective ("white") and non-reflective ("black"). Alternatively, you could use an array of IR leds (or IR reflective dots + IR light) and use dot pattern detector as opposed for checkerboard for calibration.

Regarding Hi-res cameras, the intrinsics are not calibrated and not included. It can be calibrated using our camera calibration app (voxl-camera-calibration), but you should do it at half resolution or smaller (not full size like 4056x3040), otherwise the app runs very slowly. If you need more details how to calibrate at high resolution, let me know (involves downscaling exactly by a factor of 2 and then upscaling the resulting intrinsics)

Alex

@smilon , voxl-esc-calibrate.py is a script that runs a test procedure in a single motor (with propeller mounted) to calibrate the behavior of the motor / propeller. This procedure only needs to be run once if you change motor or propeller type from a default configuration. The output of this script is just 3 coeficients a1, a2, a3 which you would need to manually enter into an ESC calibration xml file and then upload the xml paramer file to the ESC. Full details about the ESC calibration (when to do it and how) can be found here : https://gitlab.com/voxl-public/voxl-sdk/utilities/voxl-esc/-/blob/master/voxl-esc-tools/calibration.md?ref_type=heads

If you are using standard motors and propellers (one of standard ModalAI drones), you do not need to run this calibration procedure.

It sounds like you got it working, I believe voxl-configre-mpa took care of it. You can see what voxl-configure-mpa typically does here : https://docs.modalai.com/voxl-configure-mpa/ , which includes running voxl-esc to upload the latest firmware and params for a specific vehicle.

Hello @Gicu-Panaghiu,

I am going to assume you are using VOXL1, since you did not specify..

We do have RAW8 and RAW10 support for OV7251. The selection of the format has to be done in several places.

First, you have to select the correct camera driver, specifically..

ls /usr/lib/libmmcamera_ov7251*.so
/usr/lib/libmmcamera_ov7251.so
/usr/lib/libmmcamera_ov7251_8bit.so
/usr/lib/libmmcamera_ov7251_hflip_8bit.so
/usr/lib/libmmcamera_ov7251_rot180_8bit.so
/usr/lib/libmmcamera_ov7251_vflip_8bit.so

there are 5 options and one of them is _8bit.so which means it will natively ouptput 8bit data (all others output 10 bit data).

the driver name, such as ov7251_8bit has to be the sensor name <SensorName>ov7251_8bit</SensorName> in /system/etc/camera/camera_config.xml.

You can check camera_config.xml for what sensor library is used for your OV7251.

When you run voxl-configure-cameras script, it will actually copy one of the default camera_config.xml that are set up for a particular use case, and I believe it will indeed select the 8bit one - this was done to save cpu cycles needed to convert 10bit to 8bit, since majority of the time only 8bit pixels are used.

Now, you mentioned that HAL_PIXEL_FORMAT_RAW10 is passed to the stream config and unfortunately this does not have any effect on what the driver outputs. If the low level driver (e.g. libmmcamera_ov7251_8bit.so) is set up to output RAW8, it will output RAW8 if you request either HAL_PIXEL_FORMAT_RAW8 or HAL_PIXEL_FORMAT_RAW10.

So if you update the camera_config.xml to the 10bit driver and just keep the HAL_PIXEL_FORMAT_RAW10 in the stream config (then sync and reboot), you should be getting a 10 bit RAW image from the camera. But since the camera server is currently expecting 8 bit image, if you just interpret the image as 8 bit, it will appear garbled, so you will need to handle the 10 bit image (decide what you want to do with it) in the camera server.

@tonygurney , I am assuming that you are using the ESC hardware version M0134 (you can confirm using voxl-esc scan tool.

Here is the datasheet for M0134.
https://docs.modalai.com/modal-esc-datasheet/

This ESC has an option (via installing a 0 ohm resistor) to provide 3.3V to pin 1 of J3. This is the same voltage that is used for the MCUs that run on the ESC and should be used with caution (if this voltage rail is brought down by overloading, the ESC will shut down). Please see image below that shows where 0 ohm resistor should be (carefully) installed to enable 3.3V on pin1 of J3 (marked in red)

If you actually wanted 5V (VAUX), that is available on the other side of the board via two test points at the edge of the board. This voltage rail is provided by a separate switching regulator. See the following section : https://docs.modalai.com/modal-esc-datasheet/#neopixel-led-support

If you REALLY need 5V to be present on pin1 of J3, then you can add a small wire jumper from the VAUX test point directly to the pin1 of J3 (which is marked with a white dot). This pin 1 of J3 is normally disconnected. Please only do this if you are comfortable performing this type of soldering and we cannot guarantee the results :).

Alex

@KnightHawk06 , use voxl-calibrare-camera tracking_down_misp_grey <remaining options>

The ipk is available here now : http://voxl-packages.modalai.com/stable/voxl-hal3-tof-cam-ros_0.0.5.ipk - you should be able to use the launch file to choose between two modes (5=short range and 9=long range) and fps, which are listed in the launch file.

@Moderator said in VOXL ESC Mini 4-in-1 Current per Motor:

Is it possible to step up voltage?

Can you please clarify the question?

Mini ESC is designed for small drones ( < 500g ). The ESC has been tested to handle 15A continous at 15V input continuously (60+ seconds), but with full direct air flow from propellers. This would simulate a full throttle "punch-out" on a small FPV drone (high current, but also lots of direct airflow = cooling). Do not use this ESC if the drone needs 10-15A per channel just to hover. Use it in application where hover current per motor is less than 5A (ideally 2-3A which is very typical) and absolute maximum continuous current per motor can be 10-15A.

For example, motors used for small FPV drones often are around 1306 size (3-4S Lipo). Those motors are usually rated for up to 10-12A continous (for 30-60 seconds). Larger motors can be used as long as maximum motor current does not exceed 10-15A (still 2-3A at hover) and there is sufficient cooling.

Always check ESC board temperature during initial flights / tuning. Temperature must stay below 110C at all times (critical), typically in the range of 40-70C for most applications. The ESC will most likely fail above 125C.

Temperature of the ESC board is the limiting factor because the board is so small. Mosfets can handle a lot of current as long as they don't overheat. So the design of the drone is very important (either use low current so that temperature is not an issue or properly design air flow from propellers and/or add heat spreader to keep the ESC board temperature in normal range for higher current draw applications).

ESC provides real time temperature feedback and it can be viewed in PX4 / QGC. Additionally, the PX4 logs contain the temperature information.

@Rowan-Dempster ,

Please see the following commit where we recently enabled publishing the normalized frame from IMX412 and IMX664 camera via regular and ION buffers: https://gitlab.com/voxl-public/voxl-sdk/services/voxl-camera-server/-/commit/c42e2febbc6370f9bbc95aff0659718656af6906

The parameters for 1996x1520 look good, basically you will be getting 2x2 binned (full frame) and then further down-scale to 998x760. since you are doing exact 2x2 downscale in misp, you can also remove interpolation, which will make the image a bit sharper, you can see this for reference: link -- basically change the sampler filter mode from linear (interpolate) to nearest. If you use non-integer down-sample, keep the linear interpolation.

Regarding the resolution to use with VIO.. i think the 998x760 with nearest sampling should behave the same or better than AR0144 with 1280x800 resolution, mainly because the IMX412 has a much bigger lens (while still being pretty wide), so image quality is going to be better (of course, you need to calibrate intrinsics). Also the 4:3 aspect ratio may help capture more features in the vertical direction. That of course does not account for rolling shutter effects..

There can definitely be benefit in going up in resolution and using 1996x1520, but you kind of have to use the extra resolution correctly.. typically you would detect features on lower resolution image and then refine using the full resolution (also for tracking features). However, in practice, often some small blur is applied to the image to get rid of pixel noise, etc, so very fine features won't get picked up. Unfortunately, we do not know exactly what QVIO does internally. it may do some kind of pyramidal image decomposition to do these things in a smart way. You should try it and check the cpu usage.

Using MISP you can downsample and crop (while maintaining aspect ratio) to any resolution, so it's easy to experiment.

If i had to test QVIO at different resolutions, i would log raw bayer images and imu data using voxl-logger and then use voxl-replay + offline misp + offline qvio to run tests on the same data sets with different processing parameters. This may sound complicated, but it's really not:

• voxl-logger can log raw10 frames (on this branch) : https://gitlab.com/voxl-public/voxl-sdk/utilities/voxl-logger/-/tree/extend-cam-logging
• qvio relies on timestamps from incoming messages, so it can work with live data or playback data
• the only missing piece is offline MISP implementation, which is partially available in this tool : https://gitlab.com/voxl-public/voxl-sdk/utilities/voxl-mpa-tools/-/blob/add-new-image-tools/tools/voxl-convert-image.cpp -- and we are working on being able to run exactly the same implementation as in camera-server. The only missing piece in the code listed here is AWB -- however, white balance should not affect VIO too much, since only Y channel is used, so you can set white balance gains to a fixed value.
• running misp offline allows you to experiment with different resolutions / processing directly from the source raw10 bayer image (lossless)

So, if you are really serious about using hires camera for QVIO, since there are a lot of unknowns, you should consider setting up an offline processing pipeline, so that you can run repeatable tests and parameter sweeps. It requires some upfront work, but the pay-off will be significant. You can also use the offline pipeline for regression testing of performance and comparing to other VIO algorithms (which just need the MPA interface). We can discuss this topic more, if you are interested.

imx412_fpv_eis_20250919_drivers.zip are the latest for IMX412. We should really make them default ones shipped in the VOXL2 SDK, but we have not done it.

Since you are maintaining your own version of voxl-camera-server, you should add them to your voxl-camera-server repo and .deb and install them somewhere like /usr/share/modalai/voxl-camera-server/drivers. then modify the voxl-configure-camera script to first look for imx412 drivers in that folder and then fallback to searching /usr/share/modalai/chi-cdk/. In fact this is something I am considering, as maintaining camera drivers in the core system image is less flexible.

EDIT: i guess the older version of the imx412 drivers are already in the repo, so you can just replace them with new ones in your camera server repo: link

Let me know if you have any more questions. Sounds like a fun project

Alex

@Myles-Levine , if you are masking out 90% of down-facing camera, then it is probably useless any movement of the features will get it out of the unmasked region very easily and feature will be dropped.. It may hurt VIO as there may be features going in and out, only trackable for a few frames (just adds to the complexity).

You should try to move the down-facing camera to free up it's FOV or even have it facing slightly angled to the back of the drone..

Alex

Hello @Catalystmachine ,

Sorry for the confusion. We have updated the page to be more clear that Boson is not included, see below: "(No Boson)" was added to the kit description.

The title of the product already states "VOXL 2 MIPI Boson+ Adapters for Thermal IR FPV" as well as the Kit description used to say (Before we added (No Boson)) : "PCB Adapters Only..."

The price of the Boson cameras varies significantly, depending on the specifications. You can contact a distributor to get more details. For example : https://www.oemcameras.com/product-category/thermal-imaging-cameras/thermal-imaging-cores/flir-boson-series-htm/boson-plus/ (you can find more at https://oem.flir.com/contact/find-a-dealer/)

Please note that Boson+ series of the Boson sensor is required for compatibility with VOXL2.

Regarding the pricing of the adapter kit, we do offer discounts in higher volumes, if you are interested, please send us a request: https://www.modalai.com/pages/contact-us

@Kashish-Garg-1 , please see the following discussion regarding M0149 without an IR filter as well as a lens part to reference if you want to buy replacement lenses only.

If you would like to use M0149 (as opposed to M0166), the best approach would be to buy the M0149 cameras in original configuration (with IR filters) as well as additional lenses without IR filter and then swap the lenses (use contact form for a custom order with lenses). Sorry, we won't modify the standard M0149 units. I hope this helps!

Please note that lenses that are shipped with M0166 are about 1mm shorter in Z direction (along the optical axis) compared to the lenses shipped with M0149, however the lens specs are very similar. Please perform testing to ensure compatibility for your application.

https://forum.modalai.com/topic/4826/msu-m0149-1-ir-filter

Alex

@groupo , sorry, you are right, an update is overdue. Please give us a few more days to provide an official response.

Alex

Hi @austin-c ,

I ran some tests with Tmotor MN4006-23 380kV and 15-inch MS1503 propeller, using M0138 ESC. Tests were done with a battery and a power supply. Please see results below.

• the colors may vary from plot to plot, but the one with slower deceleration is "regen off"
• did not run large rpm steps on power supply because the power supply was already current limited
• regen peaks were 31V (pwm step) and 33V (rpm step) for the power supply test
• motor acceleration is almost identical for regen on/off tests
• very large difference in motor deceleration, especially for the large high-to-low rpm transitions
• also note that the power supply tests result in slower deceleration even with regen on (because the power supply cannot sink the current)
• TVS diode did not blow out in this test, because the spikes were short and only a few at a time

Please note that, in theory, it is possible to decelerate the motor faster without regenerative braking (by applying more power, but out of phase), however we do not have this implemented.

If the motor deceleration is slowed down due to lack of regenerative braking, the attitude control will be affected because the motor response is highly asymmetric for acceleration vs deceleration. Overall, this will result in effectively reducing the average responsiveness of the motor, so you would need to decrease control gains and probably will not be able to handle large disturbances very well and cause oscillations if not tuned properly.

Please review the plots (which are not surprising), and we can discuss further..

Alex

6S battery, Power step test:

6S battery, RPM small step test

6S battery, RPM large step test

11A Power Supply, Power step test:

11A Power Supply, RPM small step test

@Myles-Levine ,

You should not have any unmasked static objects appear in the camera view because they may have features that will be tracked and will confuse the algorithm because these features will be stationary with respect to the drone even if the drone is moving.

open vins should support masking parts of the camera(s) to ignore any features in this region. I am not sure how to enable the mask, will double check with colleagues (you could also do a search..).

worst care scenario, the part of the image to be ignored should be blacked out before feeding into open vins - that would be the solution if the mask is not supported. Hopefully that is not needed and mask can be used.

Alex

@SKA , I am not sure. please disable all streams except preview and try again. specifically disable:

• small_video
• large_video
• snapshot

Double check to make sure:
en_raw_preview: true
en_preview: true
en_misp : true

It seems you have at least small_video enabled.

What camera resolution are you requesting? (preview_width, preview_height)

Alex

@ey , please send us a request via http://www.modalai.com/pages/contact-us

Alex

@austin-c , i don't have any concerns for disabling active freewheeling other than the fact that the responsiveness of the ESC will be reduced, as the RPM reduction will be purely due to air drag acting on the propeller (and small friction in the motor).

I can set up the MN4006 motor with a 13 or 15 inch propeller, do a RPM control tune and compare the RPM response results with regen on and off. This is actually pretty quick to do, i will try to do it in the next few days.

Please ping me if you don't hear back by early next week

Alex