Abstract
The ability to understand why a particular robot behavior was triggered is a cornerstone for having human-acceptable social robots. Every robot action should be able to be explained and audited, expected and unexpected robot behaviors should generate a fingerprint showing the components and events that produce them. This research proposes a three-dimensional model for accountability in autonomous robots. The model shows three different elements that deal with the different levels of information, from low-level such as logging to a high level, such as robot behavior. The model proposes three different approaches of visualization, one on command line and two using GUI. The three-level system allows a better understanding of robot behaviors and simplifies the mapping of observable behaviors with accountable information.
The research described in this article has been partially funded by addendum 4 to the framework convention between the University of León and Instituto Nacional de Ciberseguridad (INCIBE).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
References
Attard, J., Orlandi, F., Scerri, S., Auer, S.: A systematic review of open government data initiatives. Gov. Inf. Q. 32(4), 399–418 (2015)
Bihlmaier, A., Hadlich, M., Wörn, H.: Advanced ROS Network Introspection (ARNI), pp. 651–670. Springer International Publishing, Cham (2016)
Butin, D., Chicote, M., Le Métayer, D.: Log design for accountability. In: 2013 IEEE Security and Privacy Workshops, pp. 1–7. IEEE (2013)
Carolan, L.: Open data, transparency and accountability: topic guide. GSDRC, University of Birmingham, Birmingham, UK (2016)
Bohren, J.: SMACH Viewer (2018). http://wiki.ros.org/smach_viewer. Accessed 29 Aug 2019
Kapitanovsky, A., Maimon, O.: Robot programming system for assembly: conceptual graph-based approach. J. Intell. Robot. Syst. 8(1), 35–62 (1993)
Lima, O., Ventura, R.: ICAPS-2018 Tutorial on Integrating Classical Planning and Mobile Service Robots using ROSPlan (2018). https://github.com/oscar-lima/rosplan_tutorial. Accessed 29 Aug 2019
Manso, L.J., Bustos, P., Bachiller, P., Núñez, P.: A perception-aware architecture for autonomous robots. Int. J. Adv. Robot. Syst. 12(12), 174 (2015)
Oreback, A.: Components in intelligent robotics. MRTC report ISSN, pp. 1404–3041 (1999)
Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, Kobe, Japan, vol. 3, p. 5 (2009)
Rodríguez, V., Rodríguez, F.J., Matellán, V.: Localization issues in the design of a humanoid goalkeeper for the RoboCup SPL using BICA. In: 11th International Conference on Intelligent Systems Design and Applications, pp. 1152–1157 (2011)
Rodríguez-Lera, F.J., Guerrero-Higueras, Á.M., Martín-Rico, F., Gines, J., Sierra, J.F.G., Matellán-Olivera, V.: Adapting ROS logs to facilitate transparency and accountability in service robotics. In: Robot 2019: Fourth Iberian Robotics Conference, pp. 587–598. Springer International Publishing, Cham (2020)
Schwarz, M.: Rosmon (2018). http://wiki.ros.org/rosmon. Accessed 29 Aug 2019
Shishkov, B., Hristozov, S., Janssen, M., van den Hoven, J.: Drones in land border missions: benefits and accountability concerns. In: Proceedings of the 6th International Conference on Telecommunications and Remote Sensing, pp. 77–86 (2017)
Thomas, D., Scholz, D., Kruse, T., Blasdel, A., Saito, I.: RQT common plugins (2013). http://wiki.ros.org/rqt_common_plugins. Accessed 29 Aug 2019
Van Harmelen, F., Lifschitz, V., Porter, B.: Handbook of Knowledge Representation, vol. 1. Elsevier, Amsterdam (2008)
Willow Garage, Inc., Maye, J., Kaestner, R.: ROS-system-monitor (2015). https://github.com/ethz-asl/ros-system-monitor. Accessed 29 Aug 2019
Xiao, Y.: Flow-net methodology for accountability in wireless networks. IEEE Netw. 23(5), 30–37 (2009)
Xiao, Z., Kathiresshan, N., Xiao, Y.: A survey of accountability in computer networks and distributed systems. Secur. Commun. Netw. 9(4), 290–315 (2016)
Yoon, M.K., Shao, Z.: ADLP: accountable data logging protocol for publish-subscribe communication systems. In: 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS), pp. 1149–1160. IEEE (2019)
Zender, H., Mozos, O.M., Jensfelt, P., Kruijff, G.J., Burgard, W.: Conceptual spatial representations for indoor mobile robots. Robot. Auton. Syst. 56(6), 493–502 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Rodríguez-Lera, F.J., González Santamarta, M.Á., Guerrero, Á.M., Martín, F., Matellán, V. (2021). Traceability and Accountability in Autonomous Agents. In: Herrero, Á., Cambra, C., Urda, D., Sedano, J., Quintián, H., Corchado, E. (eds) 13th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2020). CISIS 2019. Advances in Intelligent Systems and Computing, vol 1267. Springer, Cham. https://doi.org/10.1007/978-3-030-57805-3_28
Download citation
DOI: https://doi.org/10.1007/978-3-030-57805-3_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-57804-6
Online ISBN: 978-3-030-57805-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)