@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.

@jakkkkobo ,

The source code of voxl-send-neopixel-cmd test tool is here : https://gitlab.com/voxl-public/voxl-sdk/services/voxl-io-server/-/blob/master/tools/voxl-send-neopixel-cmd.c

The function that creates a binary packet (which is forwarded to the ESC via PX4) is here : https://gitlab.com/voxl-public/voxl-sdk/services/voxl-io-server/-/blob/master/lib/modal_io.c#L181 . Basically you need to provide the following information to this function:

• number of LEDs you are controlling
• LED type (RGB or RGBW)
• array of LED colors (3 bytes for each LED in case of RGB, or 4 bytes per LED for RGBW).
• the array should contain all LED values ranging from 0-255, so if you had 3 LEDs and first should be red, second green and third blue (50% power), the LED color array would be : [127, 0, 0, 0, 127, 0, 0,0,127].
• this function will create a packet with checksum and send it to PX4, and PX4 will forward the packet to the ESC.

You can modify the voxl-send-neopixel-cmd to do what you need, maybe you can make it accept an array of LED color values via command line.

I know the tool could have been more helpful. If you describe your use case, maybe I can help improve the voxl-send-neopixel-cmd tool.

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.

Hello @Gerhold-Ten-Voorde ,

This is not related to the quality, but instead, it is a supply chain decision.

Alex

@jbiscan21 , yes you can add the TOF sensor to Starling 2 Max, but you will also need a new front plastic mount that will hold the hires and tracking cameras as well as the new TOF sensor.

You can order the mount (which will be a drop in replacement for the original camera mount) with the TOF sensor. If you do want to proceed with the TOF sensor + plastics order, we will need to double check that all the necessary screws are included. You would need to send an email for a custom order to start this off and mention this thread and that we need to include mounting hardware. https://www.modalai.com/pages/contact-us

(related post : https://forum.modalai.com/topic/5157/c29-configuration)

See more detailed pictures.

Alex

@jbiscan21 , sorry i am surprised that we don't have a photo of the Starling 2 Max with the TOF mounted. Please see below. The TOF sensor is oriented vertically on the front face, right next to the front hires and tracking cameras.

If you need to mount the sensor somewhere else, you can use an available extension flex (it only works for the TOF V2 sensor) : https://www.modalai.com/products/msu-m0170

@leandro , yes we do have M0195 boards available. Please send us a contact inquiry to get a custom order (https://www.modalai.com/pages/contact-us).

The connectors J01, J23, J45 and J67 are not populated - we do not have a build with those connectors. You would need to add them yourself.

Also, we are currently not (yet) officially supporting the ToF pills on this board, there is limited internal testing being done. We may be able to provide limited support for that. If you are interested, i can find out what the status of this effort is.

MCBL-00128 we have is only 75mm, unfortunately.

There is a way to make the TOF V2 work on VOXL2 mini, however it is a bit of a hack (which temporarily enabled a transition to the new TOF V2 while using old camera connectors, which did not provide enough power).

• https://www.modalai.com/products/m0178?variant=48528287826224
• basically this configuration uses M0169 adapter (instead of M0178). https://docs.modalai.com/M0169/
• M0169 requires a power input of 5V ideally 1.5A, provided via the 2-pin JST connector. If you were using a voxl2, then you can use the provided 4-pin power cable with a split connection for the TOF sensor. In case of VOXL2 mini, since it accepts 3.8V input, you will need a separate 5V supply.
• M0169 can be connected to M0076 or M0135 camera interposers using the standard flex cables, such as M0074 (comes with this kit), M0036.

Note that if you use M0195 camera front end (or M0188), then you will not be able to use the TOF V2 because both camera connectors on voxl2 mini would be used up.

What's included in M0169 kit (from our shop page linked above)

@pmeras , the connector specs are provided here : https://docs.modalai.com/micro-coax-user-guide/ . Specifically, the connector part number is DF56C-26S-0.3V(51).

You can find some more information regarding the cable pinout for our hires camera here : https://docs.modalai.com/M0186/

We do not manufacture custom cables, just the ones used in our VOXL camera ecosystem.

Alex

@Mason-N , sorry for the delay. Please contact us via https://www.modalai.com/pages/contact-us for spare parts you cant find in the shop.

For 5-in Seeker, the propellers are the following, so you can purchase them directly from other vendors if you wish : HQProp DP5.1X4.1X3 3-blade 5.1In Poly Carbonate Propeller (it looks like we do have some in stock, as well)

Also, checking on the documentation...

Alex

@Matt69 , Do you need the additional PWM outputs to be connected via PX4? If not, perhaps connecting M0065 to a cpu uart and communicating directly would be the simplest (i can help you with that).

Do you have spare SLPI UARTs?

Not sure if PX4 would support multiple voxl2-io drivers running, i guess that should work? I don't think we have tried it. if you have spare slpi uart ports, just give it a shot? There may be a problem with two actuator drivers having the same name.

Alex

@AndrewC , sorry for the delay.

There are no hardware modifications to VOXL2 before installing it into Starling 2 Max. You would just need to configure SKU on your new VOXL2 board (https://docs.modalai.com/sku/) and just just reflash the latest SDK to start off clean. During the SDK install, there are a few steps (voxl-configure-mpa) that will load all the needed configurations for your SKU.

Please let us know if you have any issues with that.

Alex

@james-emi ,

In our voxl-camera-server, we have a default intrinsics config for the IMX412 camera / lens as follows (focal length approximation is based on a several calibrations). Basically it is a fisheye lens with about 2000px focal length at full resolution (half of that at half resolution, etc). The camera full sensor width is 4056 (hence the x principal point is exactly half of that 2028). In some cases we use slightly trimmed frame (4040 in width). But in any case, that should be enough for a good starting point.

lens_cal.width  = 4040;
lens_cal.height = 3040;
lens_cal.fx     = 1999.0;
lens_cal.fy     = 1999.0;
lens_cal.cx     = 2028.0;
lens_cal.cy     = 1520.0;
lens_cal.is_fisheye = 1;

Alex

@cguzikowski , quick question for you. For your application, does it matter how much time (reasonable) it takes to debayer the image? some of my offline processing scripts are not optimized for real-time operation, but are very flexible to use and the full resolution image from ov64b is huge and it may take a few seconds to process without optimizations.

We also have opencl code that runs offline pretty quick on an nvidia GPU, but it does not have as many tuning knobs.

I guess it all depends on whether you are using the images right on the voxl2 or just collecting and analyzing offline at a later time.

Alex