Getting Started

  1. 🤖 ODrive: Powering DPEA Projects
    1. Key Advantages of ODrive
    2. Examples of ODrive Integration in DPEA Exhibits
  2. Using this Library in Python
  3. Kivy GUI

🤖 ODrive: Powering DPEA Projects

ODrive motors are central to a variety of exhibits within the DPEA. They are a powerful, high-performance alternative to traditional stepper and DC motors, making them essential for driving our most demanding and precise projects.

Key Advantages of ODrive

ODrive controllers excel in applications requiring high dynamic performance and precise control because they drive brushless DC (BLDC) motors. Unlike open-loop stepper or basic DC motors, the ODrive system provides:

  • Torque and Speed Control: Excellent at both high speeds and when maximum torque is needed, ensuring smooth and reliable motion.
  • High Precision: Utilizes feedback from high-resolution encoders to maintain exact position, velocity, or torque, even under changing loads.
  • Energy Efficiency: BLDC motors driven by ODrive are generally more efficient than brushed or stepper alternatives, crucial for battery-powered or continuous-use exhibits.

Examples of ODrive Integration in DPEA Exhibits

ODrive motors are used in projects where strength, smoothness, and fine control are paramount. Some examples include:

  • High-Speed or High-Torque Actuators: Driving robotic arms or kinetic sculptures that require rapid, powerful, and repeatable movements.
  • Precision Gimbals and Camera Sliders: Achieving the ultra-smooth, slow, and precise motion necessary for professional-grade film equipment and automated photography setups.
  • Balancing and Stability Platforms: Providing the quick, corrective torque needed for systems like inverted pendulums or dynamic stability demonstrators.

Using this Library in Python

After you have followed the Getting Started section in ODrive Docs and have successfully controlled your motor using odrivetool, it is time to start using the odrive_helpers library.

We can install this library using a pip install:

pip3 install dpea-odrive

This library will allow you to automate the process of using odrivetool by bundling many of the commands into Python. For example, to move the motor one revolution in odrivetool we would need to do the following,

odrv0.axis0.requested_state = AXIS_STATE_FULL_CALIBRATION_SEQUENCE
odrv0.axis0.requested_state = AXIS_STATE_CLOSED_LOOP_CONTROL
odrv0.axis0.controller.config.control_mode = CONTROL_MODE_POSITION_CONTROL
odrv0.axis0.controller.input_pos = 1

But, using the odrive_helpers library we would simply need to run commands such as

axis0.calibrate()
axis0.set_pos(1)

To experiment with the odrive_helpers library, run ipython3 and follow along the various examples in the sidebar.

Kivy GUI

After you have tested each example, let us finish by making a Kivy GUI. Your goal with this GUI is to have the following –

  • A button that toggles between moving the motor 5 rotations clockwise and counterclockwise
  • A slider that controls the velocity of the motor
  • A second slider that controls the acceleration of the motor (i.e. two sliders to handle ramped velocity)
    • Consider changing your velocity slider to use ramped velocity and retrieve the acceleration value from the second slider.
  • If using a constrained motor setup (ex. lead screw with endstops), then add a button that homes the motor. You can home the motor using an endstop sensor/switch or until a wall is hit. Refer to the homing example for more info.
  • Another screen that controls the motor with trapezoidal trajectory control. Have text boxes for acceleration, target position, and deceleration plus a submit button to send the command to the motor.
  • Another screen which utilizes a GPIO pin to move the motor when a sensor or switch is activated.