# Probabilistic Reach-Avoid Value Function (PVF): A Temporal-Difference Learning Method for Computing Probabilistic Reach-Avoid Sets

- Source: arXiv cs.RO
- Published: 2026-10-21T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/w4f47eri2bhh0syxyey77kdc9
- Original: https://arxiv.org/abs/2610.28106

## Summary

Proposes a self-supervised method, the Probabilistic Reach-Avoid Value Function (PVF), for computing reach-avoid sets for robot tasks under stochastic, potentially unbounded disturbances, applicable to black-box systems. Compared with Hamilton-Jacobi reachability (HJR)-based baselines on systems of increasing complexity, up to the Hopper locomotion task, results show that when disturbances are non-adversarial, PVF's probabilistic reach-avoid sets are less conservative and more accurate than adversarial HJR sets. The method has been submitted to ICRA 2027.