The pi3hat r4.2, now in the mjbots store, has only minor hardware changes from the r4 and r4.1 versions. What has changed in a bigger way is the firmware, and the software that is available to interface with it. The interface software for the previous versions was tightly coupled to the quad A1s overall codebase, that made it basically impossible to use with without significant rework. So, that rework is what I’ve done with the new libpi3hat library:
I’ve now got the last custom board from the quad A1 up in the mjbots store for sale, the mjbots pi3 hat for $129.
This board breaks out 4x 5Mbps CAN-FD ports, 1 low speed CAN port, a 1kHz IMU and a port for a nrf24l01. Despite its name, it works just fine with the Rasbperry Pi 4 in addition to the 3b+ I have tested with mostly to date. I also have a new user-space library for interfacing with it that I will document in some upcoming posts. That library makes it pretty easy to use in a variety of applications.
Only 1 full year after it was released, I managed to get a Raspberry Pi 4 and test it out in the quad A1. I had been delaying doing so because of reports of thermal issues. The Pi 3B+ already ran a little hot and I didn’t want to have to add active cooling into the robot chassis to get it stable.
It looks like the Raspberry Pi engineers have been hard at work because the newer firmware releases have significantly reduced the overall power consumption and thus the thermal load. In my testing so far it only seems “a little” hotter than the 3b+.
After getting a gait which looked like it could balance across the leg support line in 1D, I needed to extend that to 2D and try it out on the robot.
Extending this to two dimensions wasn’t too bad. I just did a bunch of geometry to follow the path traced out by a given 2 dimensional velocity and rotation rate, intersected with a line segment:
Given this function, the logic to select a swing target is basically the same as in the 1 dimensional case. We now create two “virtual legs”, which consist of two feet ganged together and produce a single support line. At each time instant when all legs are in stance, we look at the time remaining until each of the virtual legs would cross the center of mass at the current velocity. As soon as one hits the half-swing point, we start a swing.
Now that the mjbots.com store has qdd100 quasi direct drive servos, moteus controllers, and the new power dist board, it is time to start getting some useful accessories in stock. While each of these components comes with mating connectors, sometimes you need more or find that a cable harness you built previously needs to be scrapped. Availability of Amass connectors isn’t that great outside of the Chinese market, so I’ve now got XT30U male and female solder cup connectors up in packs of 10. Each pack is just $6.
I’m working to improve the walking gait of the mjbots quad A1. In this iteration, I wanted to tackle an incremental step towards a more fully dynamic gait, but one that will still greatly increase the capability of the machine. As mentioned last time, the current walking gait cycles between all four legs, and then alternative opposing corner legs in order to move laterally. I’d like to keep that same basic structure, but be a bit smarter about what happens during the swing phase.
Now I’ve got a machine, the mjbots quad A1, which is capable of dynamic motions, but the only gait which takes advantage of these capabilities is the pronking one. That gait has the benefit that the dynamics are very simple. The entire time that that robot is in contact with the ground, it is in contact with all 4 legs, so in that regime it is fully controllable. Since it is fully controllable up to the point of lift-off, we can ensure that there is basically zero rotational rate while the machine is mid-flight, which means that it lands with all four legs largely at the same time. Of course, pronking isn’t a very fast or efficient way of getting anywhere, so I wanted to make the first steps… I guess pun intended, towards improving the more general walking algorithm to make the machine move faster in a more robust manner.
The first feet I built for the quad A0 lasted for maybe an hour of walking before snapping off. The current design, has been much more robust - completing a lot of intensive walking and jumping. However, all things must fail:
Looking at the failure, I was surprised I used so little material in the region in question. For now, I just made it 4x thicker and we’ll see how long that lasts, although ultimately it may need to be a different design or machined instead of 3d printed.
As I am working to improve the gaits of the mjbots quad A1, one aspect I’ve wanted to tackle for a long time is improving the compliance characteristics of the whole robot. Here’s a small step in that direction.
The quad A1 uses qdd100 servos for each of its joints. The “qdd” in qdd100 stands for “quasi direct drive”. In a quasi direct drive actuator, a low gearing ratio is used, typically less than 10 to 1, which minimizes the amount of backlash and reflected inertia as observed at the output. Then, high rate electronic control of torque in the servo based on current and position feedback allows for dynamic manipulation of the spring and dampening of the resulting system.
I’ve displayed versions of this numerous times in the past (May 2019, Feb 2020, March 2020), but now I’m proud to announce that I have a productized version of the power dist and precharge board available in the mjbots store for $79.
This board has convenient connectorization for powering sub-components of your robot, and also provides a smooth pre-charge sequence so that you can safely connect a large battery to high capacitance loads. I made a short video to show it off.
