Getting Started with Robotics Control Interfaces

When you buy your first robot from the supplier, that robot generally comes with a control Interface that you can use to control the robot without code–and from the program itself, without code.

For beginners, this makes things a lot easier to get started, but there are a few things you need to know about the foundations of moving robotic arms. 

At its core, robot control is about two things:

1. Position — where the robot’s tool is in space.

2. Orientation — how that tool is angled.

   
   

Once you understand these fundamentals, programming through a robot control interface becomes much easier.

1. The Cartesian Axes (X, Y, Z)

Think of a 3D box around the robot:

• X-axis → Left ↔ Right

• Y-axis → Forward ↔ Backward

• Z-axis → Up ↔ Down

These are the linear axes (or translations). They describe where the robot’s end effector (like a gripper) is located.

When teaching interns at Blue sky Robotics, we have had more than a few people set the Z-axis far too low and have the robotic arm try to punch through a table (thankfully slowed by its collision-sensitivity–so only a loud bang as opposed to property damage from a powerful robotic arm).

2. Orientation Angles (Roll, Pitch, Yaw)

In addition to moving in space, robots need to control how their tool is oriented:

• Roll (Rx) → Rotate around X-axis (like rolling a pencil).

• Pitch (Ry) → Rotate around Y-axis (nodding “yes”).

• Yaw (Rz) → Rotate around Z-axis (shaking your head “no”).

These are the rotational axes (or orientations).

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3. 6 Degrees of Freedom (6 DOF)

A standard industrial robot arm can move in 6 Degrees of Freedom (DOF):

1. X (left-right)

2. Y (forward-backward)

3. Z (up-down)

4. Roll (rotation about X)

5. Pitch (rotation about Y)

6. Yaw (rotation about Z)

This gives the robot the ability to place its tool anywhere in 3D space, at any angle.

4. Why It Matters

• With only X, Y, Z, you can reach a point, but not control orientation.

• Adding Roll, Pitch, Yaw lets you precisely align tools — like holding a screwdriver straight, or tilting a spray nozzle at the right angle.

 Example: To pick up a bottle on a conveyor:

• X, Y, Z → Move above the bottle.

• Yaw → Align with the conveyor.

• Pitch & Roll → Match the gripper to the bottle’s shape.

5. Manual Motion Control (No Computer Vision)

When a robot doesn’t have “eyes,” it doesn’t know where things are — it only knows where you tell it to go. This is done through:

• Teach pendants → handheld controllers with joysticks and screens.

• Manual guidance → physically moving a cobot arm to positions.

• Jogging controls → moving the robot joint-by-joint with buttons or arrows.

You drive the robot to a position, then record it as a waypoint.

6. Waypoints = Robot Memory

Waypoints are like “dots on a map”:

• Move to the pick position → save it.

• Move to the place position → save it.

• The robot later replays this sequence automatically.

Since there’s no vision, these points are fixed. If the part shifts, moves, or changes shape, the robot won’t adapt, which can lead to inaccurate automation attempts or worse-damage to the product or work cell.

7. How the Robot’s Internal Controller Executes a Program

When you press “run” from the control interface:

1. The robot’s internal controller (its onboard computer) sends signals to each joint motor to move along the taught path.

2. Joint encoders (angle sensors) feed back position data, confirming the robot is moving accurately.

3. The internal controller processes this feedback and makes fine adjustments as needed, ensuring the robot follows each waypoint in sequence until the task is complete.

   
   

8. Pros & Cons of Preset Motion Control

• Pros: Predictable, precise, reliable when parts always arrive in the same spot.

• Cons: Inflexible — if objects shift, the robot still goes to the old coordinates and may miss.

  
  

👉 Manual motion control: Robots repeat pre-taught positions.

👉 Computer vision control: Robots detect the part each cycle and adjust in real time.

 9. Where Manual Control Hits Its Limits

Manual waypoint teaching works beautifully in structured environments — like a conveyor delivering parts to the exact same spot, or a CNC machine that never changes position.

But in the real world of modern manufacturing and logistics, things rarely stay perfectly consistent:

• A box might shift slightly on a pallet.

• A part might come down the line rotated or tilted.

• Products might vary in size, color, or surface finish.

• Human workers may move around in the same space, creating safety and flexibility challenges.

In these cases, a robot without perception will fail. It will move to the taught coordinates, but the object won’t be there — leading to missed picks, damaged goods, or downtime.

Enter Computer Vision

This is where computer vision becomes essential. Adding cameras and vision algorithms gives robots the ability to:

• See where a part actually is, not just where it was programmed to be.

• Adapt to shifts, rotations, or variations in size.

• Verify that the correct product was picked, placed, or packed.

• Collaborate more safely with humans by detecting their presence.

Computer vision doesn’t replace the fundamentals of axes, waypoints, and DOF — it builds on them. The robot still moves in X, Y, Z with Roll, Pitch, and Yaw, but now it adjusts those motions in real time based on what its “eyes” detect, which makes automating for a dynamic production line much more efficient. 

Takeaway

Understanding basic motion control is the first step: waypoints, translations, and orientations give you a predictable robot program.

But for automation that’s flexible, adaptive, and real-world ready, you need perception. That’s where computer vision transforms a fixed, blind sequence into a smart, resilient system.