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From the 1 of 7 linked papers with an AI index.

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7 papers

math.OC2026

Weight Certificates for Convex Multi-Objective MPC: Geometric Characterization, Construction, and Foreclosure

Hadi Hajieghrary, Benedikt Walter, Chaitanya Shinde +1

Automated-driving rulebooks rank rule violations lexicographically, and model predictive control enforces that ranking either exactly, through sequential programs per tick,…

cs.RO2026

From Operational Design Domain to Action: A Systematic Behavioral Taxonomy for Autonomous Driving

Chaitanya Shinde, Hadi Hajieghrary, Miguel Hurtado

Operational Design Domain (ODD) specifications describe where an automated driving system (ADS) is permitted to operate, but they do not prescribe what the ADS must demonstrably do…

cs.RO2026

Real-Time Rulebook-Aware Nonlinear MPC for Autonomous Driving with Priority-Biased Tiered Slacks

Hadi Hajieghrary, Benedikt Walter, Chaitanya Shinde +2

The paper introduces W‑SQP, a weighted tiered‑slack nonlinear model predictive controller that enforces multiple driving rules in real time while providing auditable per‑rule resid…

cs.RO2026

Decentralized Geometric Control for Cable-Suspended Payload Transport with Adaptive Mass Estimation

Hadi Hajieghrary, Benedikt Walter, Paul Schmitt +1

Cooperative aerial transport requires controllers that respect nonlinear manifold geometry, operate without centralized coordination, and respect operational safety constraints. To…

cs.RO2026

Re-imagining ISO 26262 in the Age of Autonomous Vehicles: Enhancing Controllability through Transferability and Predictability

Chaitanya Shinde, Hadi Hajieghrary, Paul Schmitt +3

The ISO 26262 standard defines functional safety for road vehicles through risk assessments based on Severity, Exposure, and Controllability, grounded in a human-driven vehicle par…

cs.AI2026

RECTOR: Priority-Aware Rule-Based Reranking for Compliance-Aware Autonomous Driving Trajectory Selection

Hadi Hajieghrary, Benedikt Walter, Chaitanya Shinde +2

Autonomous driving stacks must pick one trajectory from a multi-modal candidate set; choosing by model confidence ignores safety, traffic-law, and comfort constraints. We present \…