Multi Classification Pareto Optimal Disassembly Planning

Taking over dangerous tasks such as dismantling or removing defective batteries, increasing efficiency, and reducing dismantling costs are the main advantages of automating dismantling and recycling processes. This has led to the automated planning of disassembly processes being a focus of robotic research in recent years. Many solutions have been developed and tested in various applications. However, the solutions are specialized on specific criteria, such as the reduction of tool changes in order to achieve higher efficiency. Therefore, the general application of these solutions may not provide optimal results in certain situations. This paper presents a novel approach for planning the next disassembly step, considering different evaluation modules. Each module analyzes the object based on different criteria and prioritizes each component accordingly. A Pareto optimizer then selects the optimal component, considering the different priorities. The paper presents the concept and evaluates it using different object categories.