Electrical cabinets for elevators control

Before the Project: Lift Control Systems requires constant training and adaptation of assembly operations to match new requirements and provide high-quality products. The components are transported with forklifts to the assembly workstation, where operators manually assemble the cabinets and test them for potential errors. However, quality, productivity, health and safety, and environmental issues still occur, and the assembly procedure and intra-shopfloor logistics are not yet optimized. The current manual labor activities increase the overall time required for efficient production times and increase the total manufacturing costs.

With the MASTERLY solution: A hybrid human-robot collaborative shop floor to automate intra-shop floor logistics and assembly operations for the production of electrical cabinets used for lift control. An AGV with a collaborative armcollaborates with a human operator to perform logistics operations by autonomously picking and delivering components to the assembly station. The operator installs some components with the help of an AR solution, while the mobile robot assists with the installation of electrical components using vision and force control algorithms. A smart modular gripper with integrated AI decision-making adapts its shape automatically, and AI-based vision algorithms facilitate the detection of relevant parts.

Overview of KLEEMANN’s Use Case Status and Key Milestones after 1 Year in the MASTERLY Project

The KLEEMANN use case aims to transform the assembly process for electrical cabinets used in lift control systems by implementing a hybrid human-robot collaborative environment. In its first year, the project has achieved significant advancements in productivity, quality, and safety. Key components include AGVs with collaborative arms, augmented reality (AR) for operator support and robot control, and AI-powered algorithms for perception and decision-making to enhance logistics and assembly operations.

Key Milestones and Achievements:

1. AI Object Identification: A 6D pose estimation vision system, utilizing CAD files, has been implemented to identify components for electrical cabinet assembly.
2. Force-Driven Manipulation Controller: A force control mechanism was added for delicate handling of parts, particularly for din-rail assembly.
3. Dynamic Digital Twin: A dynamic Digital Twin system centralizes data from different modules, optimizing human-robot collaboration and assembly efficiency.
4. Human Perception System: To ensure operator safety, a human perception system was developed to track human presence during AGV collaboration.
5. Dynamic Task and Action Planning Allocation: A software module was created to extract CAD file data, enabling efficient task planning and allocation.
6. AR-Based Operator Support and Robot Control: An AR application provides real-time operator assistance and robot control using interactive planners and ROS2 communication.
7. Robot Programming with Motion-Primitives: A motion-primitives approach integrated with the ROS2 framework enables effective trajectory planning and collision avoidance.

For further details, please visit: KLEEMANN Use Case