# New cross-platform moteus tools!

After receiving many requests via youtube, discord, and email, I’ve finally gone ahead, bitten the bullet, and updated all of the moteus tools to be pure python and work in a cross platform manner. Now, the only thing you need to do to install pre-compiled versions of tview and moteus tool on most* platforms is:

``````pip3 install moteus_gui
python3 -m moteus_gui.tview    # (or maybe just tview)
python3 -m moteus.moteus_tool  # (or maybe just moteus_tool)``````

I’ve personally tested these on Linux, Windows, and Raspberry Pi, and others have at least verified basic operation on Macs. Python 3.7 or greater is required.

….

But wait, there’s more!

Now, both moteus_tool, tview, and the python bindings more generally can use python-can as a transport. That means tview can now be used with socketcan, pcan, and a bunch of other options. To one up that, most users won’t have to even specify any command line options, as tview and moteus tool will automatically select a fdcanusb or python-can depending upon what is available.

I’ll be updating the devkit introduction video soon, although the commands in there will largely continue working for the time being.

## Errata

• Neither pypi or piwheels has pyside2 for the Raspberry Pi, but it is packaged in Raspberry Pi OS. You can follow the instructions in git to find a recipe that works.
• To use the pi3hat, you need to also do `pip3 install moteus_pi3hat`

# moteus and socketcan

Various users have been trying to use lower-cost Raspberry Pi CAN-FD adapters for the moteus controller for some time (like this one from Seeed), but have had problems getting communication to work. I buckled down and went to debug the problem, discovering that the root of the issue was that the linux kernel socketcan subsystem calculates very sub-optimal CAN timings for the 5Mbps bitrate that moteus uses. This results in the adapters being unable to receive frames sent at the actual 5Mbps rate, but instead only slightly slower.

The solution is to manually specify the bus timings when configuring the socketcan link. This makes the MCP2518FD boards work, and also PEAK-CAN-FD USB adapters (and probably every other socketcan CAN-FD adapter) work as well. You can find the timings linked in the moteus reference documentation: https://github.com/mjbots/moteus/blob/main/docs/reference.md#bit-timings

## General socketcan improvements

As a result of all this debugging, I made some general improvements to socketcan support in all the client side moteus tools.

1. There is now a documented commandline for invoking moteus_tool from socketcan: https://github.com/mjbots/moteus/blob/main/docs/reference.md#moteus_tool-configuration
2. I released moteus and moteus_pi3hat 0.2.0 to pypi. These provide socketcan interfaces for python, transparently using them if no fdcanusb or pi3hat peripherals are found.

Thanks for everyone on discord’s patience as we worked through these compatibility issues!

# Improving the moteus update rate, part 3

Back in part 1 and part 2, I looked at problems that limited the rate at which the host computer could command the full quadruped and some of the solutions.  Now, in part 3, I’ll cover more of the solution.

## More solution steps

Previously, I switched to using PREEMPT_RT, switched bridging strategies, and optimized the turnaround of the individual servo.  Now, I’ll move on to optimizing the host software.

### 4. Host C++ software micro-optimizations

The primary contributor in the host software to the overall update rate is the time it takes to turn around from receiving a reply from one servo, to sending the next command.  I first did some easy micro-optimizations which came up in profiling.

• error_code: My implementation of error_code with strings attached was doing lots of string manipulation even when no one asked for it.  Fixing that saved a fair amount of time throughout.
• Memory allocation: There were a few sites in the code that generated packets where a persistent buffer could be used each time, instead of having to allocate a fresh one.

### 5. boost::asio

The host software was using boost::asio to interact with the serial port.  It is high performance for what it does, allowing multiple external operations to happen in the same thread, but necessarily relies on an epoll loop and non-blocking write operations.  These aren’t particularly fast in the linux kernel, and the best turnaround time on the rpi I could achieve with asio was around 80us.

I implemented a standalone proof of concept which just uses a single thread to read and write to the serial port in a blocking manner.  Doing that allowed me to get the turnaround down to around 30us.

### 6. Protocol design

The register protocol that is used for high rate control had one opcode for setting a single register, and another for setting multiple consecutive ones.  The multiple consecutive one requires an additional byte to identify how many registers are set.  The same thing is true for queries.

I shaved a byte off of the common case of both by allowing writes and reads of up to 3 registers to encode their length in the primary opcode.

With that change, the full query packet to each servo was 23 bytes, and the full reply packet was 28 bytes.

### 7. Linux serial driver latencies

With the blocking thread approach from step #5 and that thread set to real-time priority, the average turnaround was indeed 30us.  However, when run in the full control software (which does other processing as well), occasionally latencies would be in the several millisecond range.  Also, since the PL011 on the raspberry pi only has a 16 byte FIFO, reading any frames larger than that was unreliable, as the kernel didn’t always get around to servicing things fast enough.  Even with sub-16 byte frames, and a blocking reader, the kernel would still delay reads by a millisecond or so sometimes.  I believe this is because the PL011 only provides interrupt notification on even 4 byte boundaries of its FIFO, and otherwise relies on the kernel to poll it.

Well, I can poll too, so I fixed this by just disabling the kernel’s serial driver, opening up “/dev/mem” and polling the IO memory of the controller manually in a busy loop from a RT thread.  This let me get turnarounds down to 4us, and also let me receive packets of arbitrary length without loss.  See https://github.com/mjbots/mjmech/blob/master/mech/rpi3_raw_uart.h and https://github.com/mjbots/mjmech/blob/master/mech/rpi3_raw_uart.cc

### 8. Linux scheduling latencies

With the above changes, the serial port was doing fine, but linux still had problems scheduling the primary process to run with less than 1ms precision, even when it was RT priority.  To solve that, and make the serial thread a bit better performing too, I used the “isolcpus” feature of linux to exclude 2 of the 4 raspberry pi processors from normal scheduling.  Then the main thread of the application got processor 3, and the serial thread got processor 4.  With those changes, the time required to poll the full set of 12 servos is rock solid.  Here’s a plot showing the cycle time required to poll a full set of telemetry data  (but not command them, which adds a bit more time per query but doesn’t affect the variability).

## Next steps

And in the next and final post of this series, I’ll demonstrate the final result, showing all of these changes are integrated into the primary control software.

# Improving the moteus update rate, part 2

Back in part 1, I looked at the driving factors that limited the update rate of the full quadruped.  Now in part 2, I’ll cover the first half of the solution.

## Background

To begin with, there were two major paths that I could take based around the network topology.  In one path, I would remove the active bridging capability from the junction board, and rely on the Raspberry Pi to drive all the servos directly, and in the other the active bridge would stick around.  There were a number of key disadvantages to both approaches:

Passive bridge: In this model, the raspberry pi has no choice but to rapidly turn around 12 separate queries and responses.  There is no hope for parallelization.

Active bridge: Here, the junction board’s STM32 can offload the multiple queries.  However, there are two big downsides.  The first are that the data must flow across 2 separate 485 busses.  The second, and possibly more problematic, is that it only works out better if the junction board can stream a large amount of data consecutively to the raspberry pi.  In my previous experiments, I had run into what I believe was a kernel bug that killed the serial port until a power cycle upon receive overruns.  Debugging that could easily be a large project.  Implementing the active bridge would also be a lot of work, as I don’t currently have a protocol client that runs on the STM32.

My initial back of the envelope calculations, surprisingly, indicated that both approaches could potentially get up to 250 or 300Hz with sufficient margin to still do other things.  I had expected that parallelization would win the day, but it turned out that duplicating the data across both busses had the potential to completely negate that advantage.

## Solution steps (first half)

### 1. RT_PREEMPT

The first thing I did was to switch to using a RT_PREEMPT enabled kernel with the governors set to performance.  This by itself reduced the Raspberry Pi’s reply to query turnaround from 200us to 100us.  I wanted to at this time also upgrade to the 4.19 kernel, as I hoped that it would have some fixes for high serial rates.  However, it doesn’t look like anyone has a RT enabled 4.19 kernel that supports USB and ethernet, both of which are moderately useful on a board with not many other interfaces.

### 2. “Passive” bridging

In lieu of spinning a new board right away, I instead modified the firmware of the junction board to remove almost all functionality and instead just busy loop shoving individual bytes around between the interfaces.  It is fast enough to just barely be able to achieve this at 3Mbit if interrupts are off.  The downside is that the IMU won’t be usable.  To fix that, I’ll have to spin a new board that just passively wires all the busses together and dangles the STM32 off the bus like any other node and hope that the star topology won’t matter over such short distances.

Doing this removed the double transmission penalty, as well as the additional 90us latency in the junction board on all transfers.  This, combined with RT_PREEMPT, got the overall cycle time down to about 6727us, or ~150Hz.

### 3. Controller turnaround time

Next, I started in on the moteus firmware, in order to improve the turnaround time between when a query is sent, and when the corresponding reply is generated.  This resulted in many optimizations throughout the code.  The first set were made to the primary control ISR, which runs at 30kHz currently.  Tiny improvements here make everything else run much faster.

• Constructors: The ARM gcc toolsuite, regardless of the optimization level, seems to implement a constructor of an all zero structure as a call to memset.  This is true even if the structure is a small number of bytes.  There were several places in the firmware where a structure was zeroed out by calling its default constructor.  Switching that to a “clear” method which manually assigned all the fields drastically reduced the time spent there.
• Appropriate types: When calculating a smoothed velocity, the filter was using an int64_t as an intermediate variable, which is not very efficient on an ARM.  Nothing more than an int32_t was actually needed.
• fmod: I was wrapping between zero and two pi by using fmod.  The cases where wrapping occurs were never more than one or two phases off, so just dividing and truncating was much faster with no appreciable loss of precision.
• Pre-computing some variables: Some of the calculations done in the ISR were repeated unnecessarily, so now they are on re-computed upon a configuration change.
• Make debug output optional: The moteus board has a high rate RS422 debug output, which is only rarely used.  I added a configuration knob to turn it off when not in use.
• SPI overhead: I was using the ST HAL API to access the position sensor over SPI.  I still do that for setup, but now just twiddle the raw registers to do the actual transfer, which saves a little bit of overhead in the HAL.
• SPI frequency: The AS5047P has a nominal SPI frequency limit of 10MHz.  I asked the HAL for 10MHz, but the closest it could actually do was 6MHz.  I decided to brave some flakiness and upped it to 12MHz to shave another microsecond off.

After these changes, the ISR uses around 7-8us when stopped, and around 13us per iteration when in position control mode, or around 40% of the CPU budget.

Next I made more optimizations to the software which runs in the main loop:

• StaticFunction: I was using a home-grown solution to a bounded size type-erased function callback that wasn’t particularly fast.  I switched it out for the SG14 inplace_function from github, modified to allow shrinking to a smaller type.  That sped up everything in the main loop by a fair amount.
• Protocol parsing: A number of steps in the protocol parsing and emitting eventually delegated to a call to “memcpy” into a particular type.  I broke some abstractions so that all that parsing and emitting eventually compiles down to just loads and stores.
• Reply encoding: The RS485 register protocol allows clients to query multiple consecutive registers.  As a shortcut, the server was responding to those with a series of single register replies.  I fixed that by implementing sending multiple replies at once to shave off a few bytes and some processing.

I experimented with using the STM32F446’s built in CRC unit, however it only implements a fixed CRC-32 variant.  So updating that would have required reflashing all my bootloaders.  Using that is probably best taken by updating to an STM32F7 or STM32G4 which have more configurable CRC units.  I also tried hand assembling an optimized version of the CCITT16 checksum I was using, but was only able to achieve the same 8 cycles per byte that boost already had.

With all of these changes, the average turnaround time for a single servo was down from 140us to in the 70-80us range for a full control update.

## Next steps

Coming up, in part 3, I’ll cover the remainder of the steps I took to improve the overall update rate.

# Improving the moteus update rate, part 1

The moteus brushless controller I’ve developed for the force controlled quadruped uses an RS485 based command-response communication protocol.  To complete a full control cycle, the controlling computer needs to send new commands to each servo and read the current state back from each of them.  While I designed the system to be capable of high rate all-system updates, my initial implementation took a lot of shortcuts.  The result being that for all my testing so far, the outgoing update rate has been 100Hz, but state read back from the servos has been more at like 10Hz.  Here I’ll cover my work to get that rate both symmetric, and higher.

In this first post, I’ll cover the existing design and how that drives the update rate limitations.

# Individual contributors

There are many pieces that chain together to determine the overall cycle time.  Here is my best estimate of each.

## RS485 bitrate

The RS485 protocol that I’m using right now runs at 3,000,000 baud half duplex.  That means it can push about 300k bytes per second in one direction or the other.  While the STM32 in the moteus has UARTs capable of going faster than that, control computers that can manage much faster than 3Mbit are rare, so without switching to another transport like ethernet, this is about as good as it will get.

This means that at a minimum, there is a latency associated with all transmissions associated with the amount of data, which is roughly $bytes * 10 / 3000000$.

## Servo turnaround

The RS485 protocol moteus uses allows for unidirectional or bidirectional commands.  In past experiments, all the control commands were sent in a group as unidirectional commands, then the state was queried in a series of separate command-reply sequences.  The firmware of the moteus servo currently takes around 140us from when a command finishes transmission and the corresponding reply is started.  The ideal turnaround for a bare servo is then $(txbytes * 10 / 3000000) + 140us + (rxbytes * 10 / 3000000)$.

## IMU junction board

The current quadruped has a network topology that looks like:

The junction board is an STM32F4 processor that performs active bridging across the RS485 networks and also contains an IMU.  This topology was chosen so that the junction board could query both halves of the quadruped simultaneously, then send a single result back to the host computer.  However, that has not been implemented yet, thus all the junction board does is further increase the latency of a single command.  As implemented now, it adds about 90us of latency, plus the time required to transmit the command and reply packets a second time.  That makes the latency for a single command and reply now: $2 * (txbytes * 10 / 3000000) + 110us + 90us + 2 * (rxbytes * 10 / 3000000)$

## Raspberry pi command transmission

As mentioned, the current system first sends new commands to the servos, then updates their state.  When sending the new commands, the existing implementation makes a separate system call to initiate each servos output packet.  Sometimes the linux kernel groups those together into a single outgoing frame on the wire, but more often than not those commands ended up being separated by 120us of white space.  That adds $12 * 120us$ of additional latency to an overall update frame.  So, $12 * 120us = 1440us$

## Raspberry pi reply to query turnaround

During the phase when all 12 of the servos are being queried, after each query, the raspberry pi needs to receive the response then formulate and send another query.  This currently takes around 200us from when the reply finishes transmission until when the next query hits the wire.  This is some combination of hardware latency, kernel driver latency, and application latency.  It sums up to $200us * 12 = 2400us$

## Packet framing

The RS485 protocol used for moteus has some header and framing bytes, that are an overhead on every single command or response.  This is currently:

• Source ID: 1 byte
• Destination ID: 1 byte
• Payload Size: 1 byte for small things
• Checksum: 2 bytes

That works out to a 7 byte overhead, which in the current formulation applies 12x for the command phase, and 48 times for the query phase.  12x for the raspberry pi sending, 12x for the junction board sending, and 24x for the combined receive side.  That makes a total of $(12 + 48) * 7 = 420 bytes * 10 / 3000000 = 1400us$

## Data encoding

In the current control mode of the servo, a number of different parameters are typically updated every control cycle:

• Target angle
• Target velocity
• Maximum torque
• Feedforward torque
• Proportional control constant
• Not to exceed angle (only used during open loop startup)

The servo protocol allows each of these values to be encoded on the wire as either a 4 byte floating point value, or as a fixed point signed integer of either 4, 2, or 1 bytes.  The current implementation sends all 6 of these values every time as 4 byte floats.  Additionally two bytes are required to denote which parameters are being sent.  That works out to: $((6 parameters * 4 byte float + 2) * 12 servos * 2 for junction board * 10) / 3000000 = 2080us$

The receive side returns the following:

• Current angle
• Current velocity
• Current torque
• Voltage
• Temperature
• Fault code

And in the current implementation all of those are either sent as a 4 byte float, or a 4 byte integer.  That makes $((6 parameters * 4 bytes + 2) * 12 servos * 2 for junction board * 10) / 3000000 = 2080us$

# Overall result

I put together a spreadsheet that let me tweak each of the individual parameters and see how that affected the overall update rate of the system.

I made a dedicated test program and used the oscilloscope to monitor a cycle and roughly verified these results:

Thus, with a full command and query cycle, an update rate of about 80Hz can be achieved with the current system.

Next up, working to make this much better.