Autonomous vehicle planning boosts efficiency in underground mining
Eventually Optimal and Scalable Multi-Agent Planning for Block Cave Mining
Robotics
Summary
Coordinating multiple self-driving vehicles in underground mines is very challenging because the environment and tasks change constantly. To tackle this, the authors define a new problem called Block Cave Mining that aims to move ore as efficiently as possible while following safety rules. They create two computer methods, SAMM and SAMMS, to plan vehicle routes and schedules. SAMM finds the best plan but can be slow, while SAMMS produces nearly as good plans much faster, even for big mines and many vehicles. Their experiments show that these methods can improve mining operations by better organizing autonomous fleets.
autonomous vehiclesunderground miningmulti-agent planningblock cave miningtask assignmentschedulingpath planningmixed-integer linear programmingoptimizationscalability
Authors
Christopher Leet, Paolo Forte, Uwe Köckemann, Henrik Andreasson, Sven Koenig
Abstract
Automation in underground mining has the potential to significantly enhance safety, operational efficiency, and sustainability. However, effectively coordinating fleets of autonomous vehicles in dynamic mine environments introduces substantial challenges in both optimization and motion planning. To address these challenges, we introduce and formalize the \emph{Block Cave Mining (BCM)} problem, which focuses on computing a transport plan that maximizes ore throughput while satisfying draw ratio constraints. To solve this problem, we propose SAMM, an eventually optimal anytime solver that jointly integrates task assignment, scheduling, and path planning via a mixed-integer linear programming formulation. To improve scalability, we also introduce SAMMS, a variant of SAMM that trades optimality guarantees for efficiency by decomposing the problem into shorter planning subcycles. Experimental evaluations using realistic industrial mine scenarios demonstrate that SAMMS achieves near-optimal throughput and scales effectively to larger fleets and mine layouts.