Robots Learn to Disassemble Complex Machines

Researchers at the Karlsruhe Institute of Technology in Germany have developed an adaptive robotic disassembly system. This advanced system can tackle the complex task of taking apart machines, even when encountering unexpected issues like stuck screws or missing components. Unlike traditional automation that follows strict, pre-programmed sequences, this new approach uses probabilistic planning to handle real-world uncertainties.

The robot starts with a design model but continuously analyzes how parts actually behave. If a screw is stuck, for instance, it might switch to a different tool, like a milling device, to remove it. This adaptability is crucial for dealing with machines that have been used, repaired, or may no longer match their original designs. The research was presented at the 2026 IEEE International Conference on.

This technology aims to create a more circular economy by recovering valuable components from older products instead of discarding them as e-waste. A long-term vision includes facilities with multiple robots working in tandem, essentially running an assembly line in reverse. The ultimate economic goal is to make automated repair inexpensive enough that fixing an electronic device costs less than producing a new one.