CORTEXA
← Browse
arxivmath.OCcs.RO2026-07-22

Optimal Placement of Docking Stations and Resident AUVs for Subsea Pipeline Inspection

Gabrielė Kasparavičiūtė, Pasquale Grippa, Kjetil Skaugset, Asgeir J. Sørensen, Martin Ludvigsen

A two-stage mixed-integer linear programming framework is introduced for subsea pipeline incident response planning, jointly optimizing Subsea Docking Plate (SDP) placement and resident autonomous underwater vehicle allocation to minimize both maximum and average response times under spatial uncertainty. Phase 1 minimizes the maximum response time across all potential leak locations. Phase 2 reduces the average response time subject to the maximum bound. A case study based on the Johan Sverdrup oil and gas field in Norway, with 9 SDP options and 33 pipelines, shows that just a few well-placed SDPs are enough to achieve top performance. A cost versus time Pareto analysis reveals the trade-off between deployment expenditure and response efficiency, providing actionable guidance for designing resilient and cost-effective subsea inspection networks.

View free PDFSource page

Related papers

arxivcs.ROmath.OC2026-07-02

Multi-Rate Nonlinear Model Predictive Control for Wall-Supported Bipedal Locomotion of Quadrupedal Robots

Taizoon Chunawala, Jeeseop Kim, Kaveh Akbari Hamed

This paper presents a novel layered planning and control framework based on multi-rate nonlinear model predictive control (MR-NMPC) that enables quadrupedal robots to perform hybrid bipedal locomotion with wall-assisted support in constrained environments. Real-time trajectory op…

View free PDFSource page
arxivmath.OCcs.ROeess.SY2026-07-13

LQG solution for POMDP without estimating states: A minimum variance approach

Ranjan Sarkar, Prabhat K. Mishra

This paper investigates the control of discrete-time linear time-invariant (LTI) systems subject to incomplete and corrupted measurements. Specifically, we focus on designing a Linear Quadratic Gaussian (LQG) controller without relying on explicit state estimation. By leveraging…

View free PDFSource page
arxivcs.ROmath.OC2026-07-18

ADMM-Based Safety-Critical Distributed NMPC for Cooperative Transportation by Quadrupedal Robots

Ruturaj S. Sambhus, Kapi Ketan Mehta, Yicheng Zeng, Kaveh Akbari Hamed

This paper presents a safety-critical distributed nonlinear model predictive control (DNMPC) framework for cooperative payload transportation by teams of quadrupedal robots. The proposed approach models the robotic team and the shared payload as a dynamically coupled networked sy…

View free PDFSource page
arxivmath.OCcs.ITcs.RO2026-07-18

Relative Entropy-Bounded Ambiguous Chance Constraints for Robust Planning in Nonlinear Systems

Trevor N. Wolf, Jay W. McMahon

We consider defining risk probability in stochastic control problems under distribution ambiguity. Current approaches for chance-constrained control typically assume that the true state distribution is known and Gaussian distributed. These assumptions are not amenable to many rea…

View free PDFSource page
arxivcs.ROcs.AIcs.LGeess.SYmath.OC2026-07-16

Steering Robustness into World Action Models via Mechanistic Interpretability and Optimal Control

Jihoon Hong, Julian Skifstad, Qiyue Dai, Alice Chan, Glen Chou

World Action Models (WAMs) enable semantically- and physically-informed control but are brittle under distribution shift. In this work, we use mechanistic interpretability to study how robustness-relevant perturbations are represented in WAM activation space. Comparing activation…

View free PDFSource page
arxivcs.ROmath.OC2026-07-15

Dynamical Vehicle Orienteering Problem for Multi-Rotor Unmanned Aerial Vehicles

František Nekovář, Matej Novosad, Martin Saska, Robert Pěnička

This paper introduces the Dynamical Vehicle Orienteering Problem (DVOP), a generalization of the Orienteering Problem (OP). The OP maximizes the reward collected from spatial targets under a limited travel budget; the DVOP extends it by accounting for both external and vehicle-ac…

View free PDFSource page