What is leadthrough programming in robotics?

What is leadthrough programming in robotics?

• A. A method where the work cycle is taught to the robot by simulating the motion in software.
• B. A method where the work cycle is taught by recording a demonstration in a file without moving the robot.
• C. A method where the work cycle is taught to the robot by moving the manipulator through the required motion cycle while entering the program into the controller's memory.
• D. A method where the robot learns entirely from external sensor feedback.

Answer: (C)

Leadthrough programming means you guide the robot arm through the desired motion by manually moving it, and the controller records those motions into its memory. As you move the manipulator through the required cycle, the system captures the positions (and often timing, speeds, and tool orientation) and saves them so the robot can replay the exact path later. This teach-in approach is intuitive for simple tasks and is typically done with a teach pendant or by hand-guiding the arm. It isn’t about simulating the motion in software, nor about recording a demo without moving the robot, and it isn’t about the robot learning purely from external sensor feedback. Those other methods involve offline programming, recorded demonstrations lacking real motion data, or autonomous learning from sensors, respectively.

Leadthrough programming means you guide the robot arm through the desired motion by manually moving it, and the controller records those motions into its memory. As you move the manipulator through the required cycle, the system captures the positions (and often timing, speeds, and tool orientation) and saves them so the robot can replay the exact path later. This teach-in approach is intuitive for simple tasks and is typically done with a teach pendant or by hand-guiding the arm.

It isn’t about simulating the motion in software, nor about recording a demo without moving the robot, and it isn’t about the robot learning purely from external sensor feedback. Those other methods involve offline programming, recorded demonstrations lacking real motion data, or autonomous learning from sensors, respectively.