Archives: Control

Higher speed gait formulation

As hinted in my earlier video I’ve been working towards some higher speed gaits with the quad A1. To accomplish that, I had to restructure the gait sequencing logic to permit changing cycle times and allow flight phases.

For now, I’ve tentatively broken down the trot gait into 5 regimes, based on how fast the machine is moving:

  1. At the slowest speeds, the flight legs swing through a step in the configured maximum flight time. The interval between flight times is fixed at a configured maximum. Here the speed is determined by how far the flight legs move.
  2. Once the flight legs are moving through their maximum allowed distance, then the amount of time spent with both legs on the ground is reduced in order to increase speed.
  3. At the point when both legs are not on the ground at the same time, then there begins to be a flight phase. Increasing the length of the flight phase increases the speed.
  4. When the flight phase reaches a configured maximum, then the swing time is decreased until it reaches a configured minimum.
  5. When the swing time is at a configured minimum, the flight time is at a configured maximum, and the legs are moving through their maximum range, then the machine is moving at its maximum speed.

Depending upon the current commanded rotation rate and translation velocity, the distance available for the legs to travel through may change. This uses the same mechanism from the step selection technique to determine the maximum distance at each update cycle, then selects which of the above regimes is active based on the commanded speed.

Trotting with a flight phase

Here’s another short video only update, I’ve been experimenting with flight phases on the quad A1. With the gait formulation as I have it now, it isn’t terribly stable, but with some coaxing videos are possible:

Unlimited rotations for moteus

The moteus controller has always supported multiple turns when counting positions. It has a one-revolution magnetic encoder built in, but after turn on, it keeps track of how many turns have occurred. However, if you’ve followed previous moteus tutorials, you have probably noticed a persistent caveat that for accurate control, the position of the output shaft needs to stay within a hundred revolutions of 0.0 or so. Now, I’ll describe why that was, and what I’ve done to remove the limitation, allowing unlimited rotations!

New "stay within" control mode for moteus

At the request of @nichols in discord, I’ve recently implemented a new control mode in the moteus controller, “stay within”. In this mode, as long as the controller is inside the currently commanded bounds, only a feedforward torque is commanded. When either of the optional lower or upper bound is violated, the normal PID controller is used to force the position back to the bound.

Here’s a quick video demo:

Note that this could have been roughly accomplished in a couple of ways by a higher level controller – either by monitoring the position and commanding zero kp/kd scales when inside the boundary, or just solely commanding feedforward torques based on position sensing. However, this approach lets the control run at the full 40kHz of the moteus controller, which results in much smoother operation at the boundary condition.

Optimizing moteus FET drive strength

The moteus controller uses a DRV8323 smart driver IC to drive the power MOSFETs as well as provide various safety functions. One of the capabilities it has which has so far been unexplored in moteus is its ability to control the drive strength and dead time through software configuration.

In a switching power supply or switching motor inverter, MOSFETs are arranged in a half bridge configuration. Depending upon the type of converter, one or more half bridges are used (3 phase inverters like moteus use 3 of them). Each “half bridge” has two MOSFETs, one connected between positive power and the output terminal, and the other connected between the output terminal and ground.

Improved low speed step selection

In my original series on balancing while walking, (part 1, part 2, part 3), I described some heuristics I used to handle changing directions. That was minimally sufficient in 1D, however in 2D it still leaves something to be desired, as there are more possible degenerate cases. The biggest is when spinning in place. There, the center of mass doesn’t really move at all relative to the balance line, but we still need to take steps!

Cartesian leg PD controller

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.

Existing compliance strategy

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.