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

arXiv 2602.07924 ↗First posted 8 Feb 2026cs.RO cs.AI math.OCcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 36 references that are in the map. First posted on arXiv 8 Feb 2026.

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References · 4

  1. 2021NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challengecited by 32
  2. 2022Cybersecurity Challenges in the Offshore Oil and Gas Industry: An Industrial Cyber-Physical Systems (ICPS) Perspectivecited by 1
  3. 2023Coordinated Multi-Robot Shared Autonomy Based on Scheduling and Demonstrationscited by 1
  4. 2024A System for Human-Robot Teaming through End-User Programming and Shared Autonomycited by 1

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