Optimized Human-Robot Co-Dispatch Planning for Petro-Site Surveillance under Varying Criticalities

TL;DR

This paper introduces a new optimization model for human-robot co-dispatch in petro-site surveillance, balancing efficiency, human oversight, and infrastructure criticality, with promising results for different operational scenarios.

Contribution

It formulates the HRCD-FLP, integrating tiered infrastructure criticality and supervision constraints, and evaluates heuristic solutions for large-scale problems.

Findings

Transitioning from conservative to autonomous supervision reduces costs significantly.

Exact methods outperform heuristics on small problems in cost and time.

Heuristic solutions achieve feasible results within 3 minutes with about 14% optimality gap.

Abstract

Securing petroleum infrastructure requires balancing autonomous system efficiency with human judgment for threat escalation, a challenge unaddressed by classical facility location models assuming homogeneous resources. This paper formulates the Human-Robot Co-Dispatch Facility Location Problem (HRCD-FLP), a capacitated facility location variant incorporating tiered infrastructure criticality, human-robot supervision ratio constraints, and minimum utilization requirements. We evaluate command center selection across three technology maturity scenarios. Results show transitioning from conservative (1:3 human-robot supervision) to future autonomous operations (1:10) yields significant cost reduction while maintaining complete critical infrastructure coverage. For small problems, exact methods dominate in both cost and computation time; for larger problems, the proposed heuristic achieves feasible solutions in under 3 minutes with approximately 14% optimality gap where comparison is possible. From systems perspective, our work demonstrate that optimized planning for human-robot teaming is key to achieve both cost-effective and mission-reliable deployments.