More on mapping

It’s been a frustrating week – despite lovely weather, lots broke, and once each was fixed, something else would break.  To top is all, an update to the latest version of Jessie yesterday locked the RPi as soon as I kicked off a passive flight.  I backed this ‘upgrade’ out as a result.  I now I have everything back and working, confirm by hover and 10m lateral flights this morning, although the latter aborted half-way through with an I2C error.  Underlying it all is power to the GLL and RPi 3B – I was seeing lots of brown-out LED flashes from the B3 and lots of I2C and GLL errors.  I’m consider swapping back to a 2B+ overclocked to 1.2GHz as a result.

In the meantime I have been looking at mapping in more detail as it’s complex and it needs breaking down into easy pieces.  Here’s the general idea:

Polystyrene block layout

Polystyrene block layout

Each polystyrene block is 2.5m long, 1.25m high and 10cm thick.  They are pinned together with screw-in camping tent pegs.  The plan is to

  • fly 10m  at 1m height without the ‘maze’, logging compass and GPS to check the results, in particular to see whether
    • GPS can be gently fused with RPi ground facing motion tracking to enhance lateral motion distance measurements
    • compass can be fused with IMU gyro yaw rate to enforce a better linear flight
  • fly 10m without the ‘maze’ again but with fused compass and GPS (assuming the above is OK)
  • add the ‘maze’ and fly in a straight 10m line from bottom to top again as a sanity check
  • add the Sweep and log it’s contents when doing the same 10m again
  • build the flight map in Excel based upon GPS, compass and sweep logs – the results should look like the map with the addition of what garden clutter lies beyond the end of each exit from the ‘maze’
  • add a new mapping process to do dynamically what has been done in Excel above
  • add object avoidance from Sweep and repeat – this is the hardest bit as it introduces dynamic updates to preconfigured flight plans
  • add ‘maze’ tracking code to reach a target GPS position, nominally the center of the ‘maze’ – this stage requires further thought to break it down further.

£55.71 import duty* later…

and this is what UPS handed over to me in return.

Scanse Sweep 2D LiDAR tracker

Scanse Sweep 2D LiDAR tracker

First impressions are extremely good which bodes well for meeting my high requirements and expectations.  The box is sturdy, and the contents are not going to get damaged in transit; in addition to the Sweep itself, there’s

  • a custom UART / USB adaptor that’s small and slick
  • one USB A to micro-B for a PC connection – as cables like this go, this is probably the slickest looking I’ve seen – flat cable with very tidy connectors
  • one JST to bare wires to add your own connection – this is probably what I’ll be using to attach to the RPi UART ttyAMA0 as its the same wires that my Garmin LiDAR-Lite uses so I have spares
  • one cable I have no idea what it’s for – JST at one end clearly for the Sweep, but no idea what the other end’s for
  • a sticker, oddly requiring microwaving to make it sticky – I’ll be keeping this boxed!
  • a quick start guide.

I’m not in a rush to install it on Hermione; it’s too expensive to risk while I’m busy testing out the GPS, compass and yaw code – but I will put together a basic system, probably on my piPad.  That’ll let me check whether my double 2.4A battery bank is sufficient for both a B3 and the 0.5A the Sweep needs – I suspect this will be the first problem I’ll be having to fix; certainly, the raw Garmin LiDAR already runs off it only 2.4A feed due to power problems.


*I’m glad we are part of the EU and the free trade agreement means there is no import duty – oh no, wait, feck, argh – BREXIT! }:-{(>

Still stuck

Hermione is still causing trouble with yaw control flights despite lots of refinements.  Here’s the latest.

Hermione's troubles

Hermione’s troubles

@3s she’s climbed to about a meter high and then hovered for a second.  All the X, Y, and Z flight plan targets and sensor inputs are nicely aligned.

The ‘fun’ starts at 4 seconds.  The flight plan, written from my point of view says move left by 1m over 4 seconds.  From Hermione’s point of view, with the yaw code in use, this translates to rotate anti-clockwise by 90° while moving forwards by 1m over 4 seconds.  The yaw graph from the sensors shows the ACW rotation is happening correctly.  The amber line in the Y graph shows the left / right distance target from H’s POV is correctly zero.  Similarly, the amber line in the X graph correctly shows she should move forwards by 1m over 4s.  All’s good as far as far as the targets are concerned from her and my POV.

But there’s some severe discrepancy from the sensors inputs POV.  From my POV, she rotated ACW 90° as expected, but then she moved forwards away from me, instead of left.  The blue line on the Y graph (the LiDAR and ground-facing video inputs) confirms this; it shows she moves right by about 0.8m from her POV.  But the rusty terracotta line in the Y graph (the double integrated accelerometer – gravity readings) shows exactly the opposite.  The grey fusion of the amber and terracotta cancel each other out thus following the target perfectly but for completely the wrong reasons.

There are similar discrepancies in the X graph, where the LiDAR + Video blue line is the best match to what I saw: virtually no forward movement from H’s POV except for some slight forward movement after 8s when she should be hovering.

So the net of this?  The LiDAR / Video processing is working perfectly.  The double integrated IMU accelerometer results are wrong, and I need to work out why?  The results shown are taken directly from the accelerometer, and double integrated in excel (much like what the code does too), and I’m pretty convinced I’ve got this right.  Yet more digging to be done.

In other news…

  • Ö has ground facing lights much like Zoe had.  Currently they are always on, but ultimately I intend to use them in various ways such as flashing during calibration etc – this requires a new PCB however to plug a MOSFET gate into a GPIO pin.
  • piNet has changed direction somewhat: I’m testing within the bounds of my garden whether I can define a target destination with GPS, and have enough accuracy for the subsequent flight from elsewhere to get to that target accurately.  This is step one in taking the GPS coordinates of the centre of a maze, and then starting a flight from the edge to get back there.

That’s all for now, folks.  Thanks for sticking with me during these quiet times.


P.S. I’ve got better things to do that worry about why everything goes astray @ 7s, 3s after the yaw to move left started; it’s officially on hold as I’ve other stuff lurking in the background that’s about the flower.

POV

The problem: the camera point of view is in the quad frame; the garmin point of view is in the earth frame.  They need to both be in the same frame to produce a vector that’s meaningful.  A pretty radical rewrite of this area last night resulted.  A test flight this morning sadly was pretty much the same as yesterday: a very stable hover, but shooting off right when she should have gone left.  More stats:

POV

POV

The top pair of accelerometer vs camera show pretty good alignment, right up to the point of 0.4m to the right.  I believe this is correct, but I wouldn’t put money on it yet!

The middle pair are accelerometer vs LiDAR height over time, which is excellent.

The bottom pair are the flight plans in earth and quad frames (the quad one is simply the earth one rotated from my to her POV) – this is where there’s clearly a problem – they should be the same but they are wrong once the flight rotates.  I can’t see an obvious bug in the code, which makes me suspect there’s an obvious bug in my understanding instead.

Doesn’t bode well

I’ve been tinkering with the existing PCB layout (shown below) to see if power supply changes fix the Garmin LiDAR Lite (GLL) I²C interference.

Hermione's closeup

Hermione’s closeup

I’ve basically removed the black cuboid 1.5A 5V switching power regulator using the space instead to add a 680uF electrolytic capacitor between 5V and ground near the GLL as specified in the docs.  I then powered her up directly via the PCB, rather than indirectly via the RPi micro USB 5V output GPIO pin.  I used a lab power supply which can handle up to 5A.

Hermione showed identical I²C errors with the GLL plugged in, even if not used.  The PSU showed only 0.45mA at boot, 0.5mA with Hermione’s code running passively, and about 0.6A while she was ‘flying’.  This strongly suggests the new PCB won’t solve the problem either.  I am running out of fingers to cross 🙁

The option of using the GLL PWM output is still open, but I’m not keen to swap over to using the pigpio library this requires as it uses a daemon process in the background, unlike RPi.GPIO and RPIO which both directly access the /dev/gpio devices.  I wonder how hard it would be to write my own PWM C library with python wrapper to epoll the GLL PWM pin?  It would require a new PCB revision as would pigpio so there’s a PITA there too.  For some reason, probably because this all just works on Zoe, I still want to keep banging my head to solve the I²C problems.

9 flights

For the record, here’s 9 sequential flights, with each lasting 10s: 3s ascent at 0.3m/s, 4s hoverand 3s descent at 0.3m/s.  The drift is different in each.  There are actually only 8 flights in the video; the 9th is not in the video: she never took off and lost WiFi so I had to unplug her and take her indoors.  I may post it tomorrow, though it mostly consists of me grumbling quiets while I pick her up with my arse facing the camera!

Hermione had Garmin and RaspiCam disabled – videoing the ground for lateral tracking is pointless if the height is not accurately known.

On the plus side, the new foam balls did an amazingly successful job of softening some quite high falls.

End of the line?

Status:

  • Zoe works as best as she can, but she doesn’t have the performance to run the video above 480 x 480 pixels at 20 fps.  This means lateral motion over the IKEA play mat works, but not on the gravel on the drive, never mind the grass.  I have found a micro-USB GPS dongle which I may add but I’ve yet to find a micro-USB hub to allow power, WiFi and GPS to go into the single micro USB port (the other is blocked by the frame)
  • Hermione can process video macro-blocks at 640 x 640 pixels @ 20 fps (and perhaps higher) which may be enough for the gravel drive, but I’m completely out of ideas for the source of the I²C errors from the Garmin LiDAR-Lite V3 when it is connected even if it’s not run.

I’ll continue working on the I²C to the end of the month, but after that I’ll be downing drone development and move on to other things, probably still Pi related nonetheless.

Garmin LiDAR-Lite interrupts

Here’s what I’ve captured from my scope.

LiDAR interrupts

LiDAR interrupts

It’s mostly at 2.5V with 3.3V peaks at 50ms or 20Hz corresponding to the LiDAR sampling frequency.

So the interrupt is kind of working, except the GPIO pull down is not ‘hard enough to get the 2.5V down to 0V.  Because of that, the GPIO rising edge code isn’t capturing these tiny interrupt peaks.

This suggests the LiDAR output isn’t floating as the spec implies, but has a pull-up which is lower resistance than the GPIO pull down resistor.  Seems I need to add an explicit pull-down resistor to aid the GPIO pull-down internal resistor.  Time to find out what that is.


P.S. The internal GPIO pull up/down resistor is apparently 50k, and a quick calculation suggests that means the Garmin pull-up is about 17k – this results in the base-level 2.5V shown above. So I added a 10k between the interrupt and ground, as this would bring the ‘floating’ voltage to less than 50% and hopefully enough to allow the GPIO pull up/down to work. But it didn’t, it dragged everything down to near zero (including the spikes), so I removed it, but the spikes shown above had vanished, suggesting the 10k may have broken something. The Garmin is still producing height values luckily. Annoyingly, it had no effect on the I2C errors. I’m running out of ideas of what’s causing these. 🙁

Back on the wagon

I’ve flown my Mavic probably for 20 minutes over the course of 5 short flights simply to get familiar with the controls while dodging the rain showers of the last couple of days.  I’m back inside again trying to track down why Hermione has started throwing her I²C wobbly again.

Motion processing is working well, keeping processing close to the minimum 100Hz regardless of other sensor inputs – here 156 samples were processed in 1.724s.

Processing rate

Processing rate

Garmin’s height is running stably at the intended 20Hz and it’s well withing the accuracy possible for distances less than 1m

Garmin LiDAR v3

Garmin LiDAR v3

Here’s the problem though: the IMU is fine for 862 samples averaged into the 155 motion processing blocks, showing just gravity as Hermione sits on the ground, but suddenly the IMU values spike for no reason for the 156 sample average.  Note that this happens only when the Garmin is plugged in.  There are in fact two spikes: the first is shown, the second causes an I/O exception and the diagnostics are dumped:

IMU stats

IMU stats

I’ve tried power supplies up to 3.4A, both battery and mains powered; I’ve resoldered various critical PCB joins; I’ve added the 680uF capacitor as the Garmin spec suggests despite Zoe being fine without it, and I’ve used a newly flashed SD card, all to no avail.

I have two things left to try:

  • currently the Garmin is read every motion processing loop, despite being updated at 20Hz; the spec says there’s an interrupt, but as yet, I’ve not got it to work.  Must try harder!
  • Failing that, I’ll have to replace the MPU-9250 with another, and see if the current one is faulty.

Beyond these two, I’m out for ideas.

The GPS + compass plan

My intent with GPS and compass it that Hermione flies from an arbitrary take-off location to a predetermined target GPS location, oriented in the direction she’s flying.

Breaking that down into a little more detail.

  • Turn Hermione on and calibrate the compass, and wait for enough GPS satellites to be acquired.
  • Carry her to the destination landing point and capture the GPS coordinated, saving them to file.
  • Move to a random place in the open flying area and kick off the flight.
  • Before take-off, acquire the GPS coordinates of the starting point, and from that and the target coordinates, get the 3D flight direction vector
  • On takeoff, climb to 1m, and while hovering, yaw to point in the direction of the destination target vector using the compass as the only tool to give a N(X), W(Y), Up(Z) orientation vector – some account needs to be taken for magnetic north (compass) vs. true north (GPS)
  • Once done, fly towards the target, always pointing in the way she’s flying (i.e. yaw target is linked to velocity sensor input), current GPS position changing during the flight always realigning the direction target vector to the destination position.
  • On arrival at the target GPS location, she hovers for a second (i.e. braking) and decends.

There’s a lot of detail hidden in the summary above, not least the fact that GPS provides yet another feed for 3D distance and velocity vectors to be fused with the accelerometer / PiCamera / LiDAR, so I’m going to have to go through it step by step

The first is to fly a square again, but with her oriented to the next direction at the hover, and once moving to the next corner, have yaw follow the direction of movement.  Next comes compass calibration, and flight plan based upon magnetic north west and up.

However, someone’s invoked Murphy’s / Sod’s law on me again: Hermione is seeing the I2C errors again despite no hardware or software changes in this area.  Zoe is behaving better, and I’m trying to double the motion tracking by doubling the video frame rate / sampling rate for the Garmin LiDAR-Lite; the rate change is working for both, but the LiDAR readings see to be duff, reading 60cm when the flight height is less than 10cm.  Grr 🙁