Barrier Certificate based Safe Control for LiDAR-based Systems under Sensor Faults and Attacks

TL;DR

This paper presents a fault-tolerant control framework for LiDAR-based autonomous systems that ensures safety under sensor faults and attacks by reconstructing and verifying sensor data and applying barrier certificates.

Contribution

It introduces a novel fault-tolerant estimation and control framework that guarantees safety of LiDAR-based systems under malicious sensor faults and attacks.

Findings

Framework successfully maintains UAV safety in urban environments.

Proven safety guarantees using control barrier certificates.

Outperforms baseline methods in fault scenarios.

Abstract

Autonomous Cyber-Physical Systems (CPS) fuse proprioceptive sensors such as GPS and exteroceptive sensors including Light Detection and Ranging (LiDAR) and cameras for state estimation and environmental observation. It has been shown that both types of sensors can be compromised by malicious attacks, leading to unacceptable safety violations. We study the problem of safety-critical control of a LiDAR-based system under sensor faults and attacks. We propose a framework consisting of fault tolerant estimation and fault tolerant control. The former reconstructs a LiDAR scan with state estimations, and excludes the possible faulty estimations that are not aligned with LiDAR measurements. We also verify the correctness of LiDAR scans by comparing them with the reconstructed ones and removing the possibly compromised sector in the scan. Fault tolerant control computes a control signal with the remaining estimations at each time step. We prove that the synthesized control input guarantees system safety using control barrier certificates. We validate our proposed framework using a UAV delivery system in an urban environment. We show that our proposed approach guarantees safety for the UAV whereas a baseline fails.