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Abstract

As autonomous robots become increasingly ubiquitous, more attention is being paid to the security of robotic operation. Autonomous robots can be seen as cyber-physical systems that transverse the virtual realm and operate in the human dimension. As a consequence, securing the operation of autonomous robots goes beyond securing data, from sensor input to mission instructions, towards securing the interaction with their environment. There is a lack of research towards methods that would allow a robot to ensure that both its sensors and actuators are operating correctly without external feedback. This paper introduces a robotic mission encoding method that serves as an end-to-end validation framework for autonomous robots. In particular, we put our framework into practice with a proof of concept describing a novel map encoding method that allows robots to navigate an objective environment with almost-zero a priori knowledge of it, and to validate operational instructions. We also demonstrate the applicability of our framework through experiments with real robots for two different map encoding methods. The encoded maps inherit all the advantages of traditional landmark-based navigation, with the addition of cryptographic hashes that enable end-to-end information validation. This end-to-end validation can be applied to virtually any aspect of robotic operation where there is a predefined set of operations or instructions given to the robot.

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Robot hazards: from safety to security
  • L A Kirschgens
  • I Z Ugarte
  • E G Uriarte
  • A M Rosas
  • V M Vilches
L. A. Kirschgens, I. Z. Ugarte, E. G. Uriarte, A. M. Rosas, and V. M. Vilches, "Robot hazards: from safety to security," arXiv preprint arXiv:1806.06681, 2018.
Secure and secret cooperation of robotic swarms by using merkle trees
  • E C Ferrer
  • T Hardjono
  • M Dorigo
  • A Pentland
E. C. Ferrer, T. Hardjono, M. Dorigo, and A. Pentland, "Secure and secret cooperation of robotic swarms by using merkle trees," arXiv preprint arXiv:1904.09266, 2019.
Blockchain-powered collaboration in heterogeneous swarms of robots
  • Peña Queralta
  • T Westerlund
J. Peña Queralta and T. Westerlund, "Blockchain-powered collaboration in heterogeneous swarms of robots," arXiv preprint arXiv:1912.01711, 2020, symposium on Blockchain for Robotic Systems, MIT Media Lab.
Security and performance considerations in ros 2: a balancing act
  • J Kim
  • J M Smereka
  • C Cheung
  • S Nepal
  • M Grobler
J. Kim, J. M. Smereka, C. Cheung, S. Nepal, and M. Grobler, "Security and performance considerations in ros 2: a balancing act," arXiv preprint arXiv:1809.09566, 2018.
Automated vehicle map localization based on observed geometries of roadways
  • B R Hilnbrand
  • P Robert
B. R. Hilnbrand and P. Robert, "Automated vehicle map localization based on observed geometries of roadways," May 14 2019, uS Patent 10,289,115.
Autocalibration of a mobile UWB localization system for ad-hoc multi-robot deployments in GNSS-denied environments
  • C Martínez Almansa
  • W Shule
  • J Peña Queralta
  • T Westerlund
C. Martínez Almansa, W. Shule, J. Peña Queralta, and T. Westerlund, "Autocalibration of a mobile UWB localization system for ad-hoc multi-robot deployments in GNSS-denied environments," arXiv preprint arXiv:2004.06762, 2020.
UWB-based localization for multi-UAV systems and collaborative heterogeneous multi-robot systems: a survey
  • W Shule
  • C Martínez Almansa
  • J Queralta
  • Z Zou
  • T Westerlund
W. Shule, C. Martínez Almansa, J. Peña Queralta, Z. Zou, and T. Westerlund, "UWB-based localization for multi-UAV systems and collaborative heterogeneous multi-robot systems: a survey," arXiv preprint arXiv:2004.08174, 2020.
Sorting system of robot based on vision detection
  • Q Qin
  • D Zhu
  • Z Tu
  • J Hong
Q. Qin, D. Zhu, Z. Tu, and J. Hong, "Sorting system of robot based on vision detection," in International Workshop of Advanced Manufacturing and Automation. Springer, 2017, pp. 591-597.
Robot Operating System (ROS)
  • A Koubâa
A. Koubâa, Robot Operating System (ROS). Springer, 2017.
Quantum preimage, 2nd-preimage, and collision resistance of sha3
  • J Czajkowski
  • L G Bruinderink
  • A Hülsing
  • C Schaffner
J. Czajkowski, L. G. Bruinderink, A. Hülsing, and C. Schaffner, "Quantum preimage, 2nd-preimage, and collision resistance of sha3," IACR ePrint, vol. 302, p. 2017, 2017.