Secure Encoded Instruction Graphs for End-to-End Data Validation in Autonomous Robots

As autonomous robots are becoming more widespread, attention is being paid to the security of robotic operations. Autonomous can be seen as cyber–physical systems: they operate in virtual, physical, and human realms. Therefore, securing operations requires not only their data (e.g., sensor inputs mission instructions) but interactions with environment. There currently a deficiency methods that would allow securely ensure sensors actuators operating correctly without external feedback. This article introduces an encoding method end-to-end validation framework for missions robots. In particular, we present proof concept map method, which allows navigate realistic environments validate operational instructions almost zero a priori knowledge. We demonstrate our using two different encoded maps experiments simulated real Our have same advantages typical landmark-based navigation, added benefit cryptographic hashes enable information validation. applicable any aspect operation there predefined set actions or given robot.