Speaker
Description
The development of next-generation tracking detectors comprises challenges in mechanical integration, high-density service routing, and long-term maintenance. As these systems become more complex and are deployed in constrained, high-radiation environments, traditional manual intervention reaches its limit.
di.monta introduces a novel approach to detector lifecycle management through robust, adaptive and AI-enhanced robotic automation. With our platform, we address the key objectives of DRD8 Work Package 1 (Global System Design and Integration), and specifically supporting Project 1.2 (Robotics in the HEP Experimental Caverns).
By utilizing our robot-agnostic orchestration di.core, we provide robotic units with our modular di.skills. Our di.skills range from high-precision detection of various components, over loosening complex mechanical connections like fasteners and connectors, to deriving adaptive task plans. Our solution is explicitly designed to handle the variable states we face in HEP experiments. For example, we enable automated decommissioning by safe, fast and precise dismantling of detectors to facilitate the circular economy through component reuse and high-purity recycling.
With the integration of our adaptive robotics, we propose a shift towards sustainable HEP engineering, where automated dismantling is considered from the initial design phase to ensure the efficient decommissioning of future collider experiments.