Secure Minimum Time Planning Under Environmental Uncertainty: an Extended Treatment
This addresses security vulnerabilities in cyber-physical systems like robots, which often neglect attack impacts on mission success, though it appears incremental by combining existing control methods.
The paper tackles the problem of secure optimal control for robotic systems under cyber attacks that compromise environmental knowledge, presenting a planner that generalizes stopping distance in 3D and analyzing its properties in simulation.
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 This work focuses on cyber attack, but the results generalize to incomplete or outdated information of an environment.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.