Secure Minimum Time Planning Under Environmental Uncertainty: an Extended Treatment

TL;DR

This paper introduces a secure optimal control algorithm for robotic systems that accounts for cyber attacks and environmental uncertainties, integrating robust control, optimal control, and sensor-based planning to enhance safety and mission success.

Contribution

It presents a novel control algorithm that ensures safety under cyber attacks and environmental uncertainties, extending traditional stopping distance concepts in 3D.

Findings

Algorithm successfully handles cyber attacks in simulation

Generalizes stopping distance to 3D environments

Analyzed properties demonstrate robustness and effectiveness

Abstract

Cyber Physical Systems (CPS) are becoming ubiquitous and affect the physical world, yet security is seldom at the forefront of their design. This is especially true of robotic control algorithms which seldom consider the effect of a cyber attack on mission objectives and success. This work presents a secure optimal control algorithm in the face of a cyber attack on a robot's knowledge of the environment. This work focuses on cyber attack, but the results generalize to incomplete or outdated information of an environment. This work fuses ideas from robust control, optimal control, and sensor based planning to provide a generalization of stopping distance in 3D. The planner is implemented in simulation and its properties are analyzed.