The process of creating robot programs involves two steps. Simulation refers to replicating automation processes within a 3D virtual environment using PC software. Offline Programming (OLP) then converts all or part of this simulation into a language that the robot controller can interpret. Finally, the process finishes in generating executable programs for the robot controller.

Understanding Project Requirements

We begin by clearly defining the specific goals of the automation project, whether it’s path planning, collision checking, minimising system downtime, or simplifying the programming process. These objectives should shape every step of the project, from setting up the virtual robotic cell to determining what should be and not be simulated. Keeping these goals in focus will also help in selecting the appropriate tools and outlining necessary steps to successfully complete the project.

Project Prerequisites

The following essentials are required before starting:

• OLP Software: A versitile platform for simulating and programming robots.
• Robot Models: Including kinematics and joint limits.
• Tooling and End-Effector Model or Data: CAD model or accurate details of grippers, welders, or other tools.
• Other mechanisms: For example, external axes, positioners, or conveyors.
• CAD Models of Relevant Objects: Parts, fixtures, Workbenches, and any other environmental components.
• Precise Measurements: Including workspace dimensions and safety zones.

Step 1 – Set up the Virtual Robotic Cell

The first step is to create a virtual representation of the robotic cell. This involves importing CAD models of the environment, including the robot, end-effectors, parts, fixtures, and other essential equipment. The level of detail can vary depending on the project. For example, a simple bounding box can be enough for collision detection purposes.

Key Tasks:

• Import CAD models of robots and environmental components.
• Configure the work cell, including tool coordinates (TCP and orientation) and user reference coordinates.
• Define safety zones, collision detection areas, and workspace boundaries if applicable.

Step 2 – Set up Targets for Path Planning

After setting up the virtual cell, the next step is defining targets, which are specific positions for the robot to reach during its operation. Targets can include tool positions and orientation, defined by 3D coordinates in the Cartesian space.

Methods to Define Targets:

• Manual Creation: Using the 3D software’s user interface to select critical points, e.g., pick-up and drop-off points.
• Extract from CAD Models: Import or extract using software interface, geometric features such as points or curves.
• Import from External Files: Import targets from data files or CAM programs, as well as tool data.

Step 3 – Path Planning and Optimisation

With targets defined, the next step involves planning the robot’s motion between these points. Path planning focuses on determining efficient, collision-free trajectories for the robot while considering speed, joint limits, and cycle time. Optimisation ensures that the robot performs smooth paths in the shortest time possible without compromising accuracy or safety.

Key Steps:

• Generate initial paths connecting the defined targets while avoiding obstacles.
• Test and refine paths for smooth and collision-free motion.
• Adjust speeds and accelerations to ensure safe and efficient operation.

Step 4 – Simulation and Programming

The final step is to simulate the entire operation to validate the robot’s performance and generate robot controller program. Simulation allows you to test the robot’s motion, detect potential issues like collisions or singularities, and fine-tune the program without affecting live production. Once validated, the program is translated into a format compatible with the robot controller for deployment.

Key Tasks:

• Run a full simulation of the robot’s motion and task sequences.
• Check for collisions, singularities, and unreachable targets.
• Generate and export the robot program in the appropriate language (e.g., RAPID, KRL, LS, Adept, etc).

Conclusion

Robotic simulation and offline programming are important in modern automation projects. A structured approach includes defining goals, setting up a virtual cell, planning optimised paths, validating through simulation, and generating controller program. As industries continue to adopt advanced automation, proficiency in OLP will become a critical asset, enabling the workforce to remain competitive and ready to embrace the future of automation.