Robotics Academy: Palletizing with an Industrial Robot Exercise

RoboticsAcademy provides browser-based robotics exercises where students write Python control logic without dealing with ROS2, simulation, or motion planning infrastructure. The existing industrial robot exercises (Pick & Place, Machine Vision) cover basic manipulation tasks but lack a palletizing exercise — one of the most common real-world industrial automation tasks. This project delivers a complete palletizing and de-palletizing exercise built on ROS2 Humble and Gazebo Harmonic, using a UR5 arm and the IFRA-Cranfield API as baseline. The exercise introduces a dynamic conveyor-fed object supply chain, programmatic pallet grid computation, multi-layer collision-aware motion planning, and a full de-palletizing sequence — all accessible through a clean Python HAL without writing a single line of ROS2 or MoveIt2 code. Deliverables include a Gazebo Harmonic simulation world with conveyor feeding assembly, an extended HAL with four new methods, a dynamic MoveIt2 collision scene, browser integration via the RoboticsAcademy interface, student and maintainer documentation — targeting a 350-hour GSoC commitment across 12 weeks.