GDPR-aware trajectory sharing for ISAC-assisted robot navigation: an FID-constrained collision prediction case study

An FID-constrained trajectory sharing scheme for ISAC-assisted robot obstacle avoidance that achieves a privacy-utility trade-off strictly better than fixed-error perturbation on real pedestrian trajectories. The scheme responds to the requirements of GDPR Articles 5(1)(c) and 5(1)(f) on data minimization and prevention of unauthorized reconstruction, perturbing perceptual estimates according to local information content before sharing. At a matched missed-conflict rate, its reconstruction leakage and sustained exposure length are both consistently lower.