TLDR: As of firmware 2026-01-21 moteus now has a maximum modulation depth that is 6% larger than before. That means the maximum speed for a given voltage is that much higher. Read on for the effort invested in making that happen.
Back in 2022 moteus added support for acceleration limited trajectories. This was a highly requested feature and has been used for all sorts of applications since. However when working on the recent trajectory optimization effort it became obvious that there were still some lingering stability issues on two fronts. First, when decelerating, there would occasionally be single control cycles where an acceleration was instead commanded. Second, termination at the end of a move would often involve small amounts of overshoot or oscillation. You can see both in one of the plots from that post here:
Acceleration instability
I’ve known about this for several years now, and occasionally have spent a few minutes trying to think of alternate formulations that would be more stable. With my recent attempts to use Claude Code, I thought maybe it could help here too since at least this part of the firmware is entirely tested by host side unit tests? Well, the answer was I suppose it did help, but not exactly in the way I originally intended. Read on for more details, or upgrade to moteus firmware 2026-01-21 if you just want the fixes.
In a mini-project inspired by a Discord chat about a Rubik’s cube solver, I decided to undertake a project to see how quickly I could get moteus to make a controlled 90 degree movement and a controlled 180 degree movement. The project ended up involving a fair amount more work and theory than I had expected, but resulted in an overall solution that is relatively close to optimal for the specified moteus and motor. If you find text too hard, you can watch the video below, otherwise read on to see the details:
Most users of the moteus brushless motor controller will perform diagnostics and monitoring over CAN-FD, using something like tview, the moteus python library or the moteus C++ library. These options are great, since CAN-FD works over long distances, allows multiple devices to be multiplexed and is relatively immune to EMI or other electrical disturbances. The biggest downside is that at best, you can capture telemetry a few thousand times a second. For instance here, 2.5kHz is the maximum achievable update rate with a pi3hat and a single moteus.
What should you do when you want to monitor events that happen faster than that? Well, moteus has a solution for that too, and while it isn’t nearly as convenient, it does get the job done for many uses. It is called “high rate debug output” and lets moteus emit small amounts of telemetry data at every single control cycle, so up to 30kHz. In this post I’ll show how to configure and use it, how to capture the resulting output, and how to plot it or otherwise make use of it.
Wow, the updates to the graphical moteus monitoring application tview just won’t stop! We’ve had a lot of changes recently (python console, fault text decoding, fault monitoring, UUID addressing) and now here is yet another long requested big quality of life improvement – recording data to log files! As of pypi moteus-gui version X, tview now can write log files in either the .jsonl format as a single file or as a set of CSV files. Continue reading for more details!
Following a brief period with no stock, we’ve restocked the original 32mm x 22mm x 4mm diametric ring magnet at mjbots.com. Additionally, there are now 4 new sizes to choose from:
This should hopefully let you use low cost (albeit low accuracy), off axis diametric ring magnets in even more applications. Good luck!
Way back in 2020, I wrote about the motor saturation model that moteus uses to accurately calculate torque when a motor is operating in a region where the stator becomes saturated. What I didn’t write about was a method for actually determining those fit parameters for a given motor. This isn’t too critical, as most position mode applications don’t require the applied torque to be terribly accurate, but in some cases it does matter. When that is the case, there is now a tool that can calculate parameters appropriate for entering into moteus. Read on to find out more!
Recent improvements to the mjcanfd-usb-1x and the pi3hat were stepping stones to improved reliability for long daisy chains of moteus controllers. Another step in that process is the feature I’ll describe here, hardware CAN ID filtering in the moteus firmware. Let’s talk about how things used to work, what the problems were and how this new feature helps.
moteus_tool has long served as the primary interface to moteus
controllers from the command line for provisioning and diagnostics,
especially so when used in headless environments where running a
graphical tool like tview is not an option. As anyone who has
debugged a moteus system from the command line can attest to, finding
the contents of diagnostic stream channels is annoying at best and
that is only if you know how to do it. In short, you have to use
--console, and then type some undocumented text incantations .
Thus a new feature in moteus_tool: the --read CHANNEL command line
flag, which reads a single instance of an arbitrary diagnostic channel
from the device, then prints it to the console as JSON formatted
structured data. Let’s check out what that looks like:
The tview graphical monitoring application has been getting a lot of work lately. First was support for enumerating controllers by UUID, then monitoring faults and graphically highlighting them and then decoding textual values for fault codes. I’m excited to announce yet another improvement for tview, this one on the larger side: an interactive python REPL (read-evaluate-print-loop)! Available now in pypi moteus-gui v0.3.93.
The bottom console now has two tabs, the first and default remains the diagnostic console, where you can see what diagnostic messages the devices are emitting and send diagnostic channel commands directly to connected devices. The new, second tab, is labeled “Python” and provides access to a fully functional Python evaluation environment with full access to the moteus python library, including asynchronous operations.
Read on to see how to use it.
