Technical framework for multi-robot unmanned mining, loading, and transportation in open-pit mines

Autonomous open-pit mining can improve operational efficiency, reduce occupational risks, and lower energy consumption. This study presents a framework for collaborative mining, loading, and transportation using multiple robots. A hierarchical scene model incorporates terrain, environmental, and path planning constraints, while a digital twin simulation platform supports static scene construction. A two-dimensional spatial model of shovel–truck loading generates loading points automatically. A multi-strategy improved adaptive ant colony optimization algorithm (MIAACO) plans truck paths, and fifth-degree non-uniform rational B-splines (NURBS) support shovel excavation trajectory planning. These components coordinate the loading workflow within a closed-loop system. We derived an efficiency model and tested the framework at an operating mine. Both the model estimates and field results indicated higher operational efficiency than conventional operation under the tested conditions. The findings support the application of coordinated autonomous systems to open-pit mining.