Skip to content

Encoder

The Encoder_MMFS class provides a standard MMFS interface for rotary or linear encoders. It inherits from Sensor and implements the familiar MMFS lifecycle (begin(), update()), while requiring only simple hardware-specific methods to be overridden.

Overview

The encoder tracks step counts — ticks of a shaft or linear scale — relative to its startup position. It is commonly used for measuring angular rotation, wheel travel, or simple mechanical motion.

Internally, the Encoder_MMFS class handles lifecycle integration and telemetry exposure. You only need to implement two functions:

1
2
bool init() override;
void read() override;
  • init() sets up your encoder hardware (e.g., pin modes, timers, interrupts)
  • read() fetches the current number of steps and updates internal variables

Inheritance Structure

Encoder_MMFS inherits from Sensor, and therefore implements:

  • begin() → Calls init() and stores whether bias correction is enabled
  • update() → Calls read() and then updates the telemetry data buffer

This ensures your encoder integrates seamlessly with MMFSSystem and the logging stack.

Exposed Data Columns

The encoder automatically registers the following telemetry column:

  • Steps (Rel Steps) – integer number of encoder steps since initialization

These are reported through the DataReporter API and appear in logs and telemetry streams.

Usage Flow

1
2
3
4
5
6
7
MyEncoder encoder;
encoder.begin();

loop() {
    encoder.update();
    int ticks = encoder.getSteps();
}

To add a hardware-specific encoder driver, subclass Encoder_MMFS and implement init() and read():

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
class MyEncoder : public Encoder_MMFS {
    MyHardwareEncoder hw;

    bool init() override {
        return hw.begin(); // or whatever init call the library uses
    }

    void read() override {
        currentRelativeSteps = hw.getSteps();
    }
};

Summary

  • Encoder_MMFS provides a standard interface for step-counting encoders
  • Override init() and read() to integrate your own hardware
  • Automatically hooks into MMFS telemetry and logging
  • Supports packed telemetry for bandwidth-sensitive applications

Written by ChatGPT. May not be fully accurate; verify against source.