Abstract
Providing an efficient logging engine to determine the causes of an event is needed to enforce humans trust in computing systems. This fact becomes increasingly challenging in robotics, where unexpected decisions can have unpredictable consequences in sensitive environments, endangering human interests. In order to analyze the causes of an incident or to anticipate future behaviors, it is necessary to record every cause of a given event. Although this task is usually developed through logging systems, characteristics such as incomplete recording of events, the inclusion of unhelpful data, or the impact on robot performance, make it necessary to conceive new accountability solutions. This work presents a generic approach to developing an accountability system that consists of four main components: a system event logger, a message producer, a distributed event streaming platform, and a database. The proposed solution has been tested in several assessment scenarios in order to define the best strategy to reduce the impact of auditing and logging tasks on robot performance.
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Anjomshoae, S., Najjar, A., Calvaresi, D., Främling, K.: Explainable agents and robots: results from a systematic literature review. In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS 2019, pp. 1078–1088. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2019)
Guerrero-Higueras, Á.M., Rodríguez-Lera, F.J., Martín-Rico, F., Balsa-Comerón, J., Matellán-Olivera, V.: Accountability in mobile service robots. In: Fuentetaja Pizán, R., García Olaya, Á., Sesmero Lorente, M., Iglesias Martínez, J., Ledezma Espino, A. (eds.) Advances in Physical Agents. WAF 2018. Advances in Intelligent Systems and Computing, vol. 855, pp. 242–254. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-99885-5_17
Gupta, A., Tyagi, S., Panwar, N., Sachdeva, S., Saxena, U.: NoSQL databases: critical analysis and comparison. In: 2017 International Conference on Computing and Communication Technologies for Smart Nation (IC3TSN), pp. 293–299 (2017)
Han, Z., Allspaw, J., Norton, A., Yanco, H.A.: Towards a robot explanation system: a survey and our approach to state summarization, storage and querying, and human interface (2019)
Kreps, J., Corp, L., Narkhede, N., Rao, J., Corp, L.: Kafka: a distributed messaging system for log processing. In: NetDB 2011 (2011)
Maruyama, Y., Kato, S., Azumi, T.: Exploring the performance of ROS2. In: Proceedings of the 13th International Conference on Embedded Software, EMSOFT 2016. Association for Computing Machinery, Inc. (2016). https://doi.org/10.1145/2968478.2968502
Niemueller, T., Abdo, N., Hertle, A., Lakemeyer, G., Burgard, W., Nebel, B.: Towards deliberative active perception using persistent memory. Technical report (2013)
Niemueller, T., Lakemeyer, G., Srinivasa, S.S.: A generic robot database and its application in fault analysis and performance evaluation. In: IEEE International Conference on Intelligent Robots and Systems, pp. 364–369 (2012)
Oliveira, M., Lim, G.H., Lopes, L.S., Kasaei, S.H., Tome, A.M., Chauhan, A.: A perceptual memory system for grounding semantic representations in intelligent service robots. In: IEEE International Conference on Intelligent Robots and Systems, pp. 2216–2223. Institute of Electrical and Electronics Engineers Inc. (2014)
Quigley, M., et al.: ROS: an open-source Robot Operating System. In: ICRA Workshop on Open Source Software (2009). http://stair.stanford.edu
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: Silva, M., Luís Lima, J., Reis, L., Sanfeliu, A., Tardioli, D. (eds.) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing, vol. 1093, pp. 587–598. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-36150-1_48
Wang, Z., et al.: Kafka and its using in high-throughput and reliable message distribution. In: Proceedings - 8th International Conference on Intelligent Networks and Intelligent Systems, ICINIS 2015, pp. 117–120. Institute of Electrical and Electronics Engineers Inc. (2016)
Winkler, J., Tenorth, M., Bozcuoğlu, A.K., Beetz, M.: CRAMm – memories for robots performing everyday manipulation activities (2014)
Xiao, Y.: Flow-net methodology for accountability in wireless networks. IEEE Netw. 23(5), 30–37 (2009)
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)
Acknowledgments
The research described in this article has been partially funded by Instituto Nacional de Ciberseguridad de España (INCIBE), under the grant “ADENDA 4: Detección de nuevas amenazas y patrones desconocidos (red Regional de Ciencia y Tecnología)”, addendum to the framework agreement INCIBE-Universidad de León, 2019–2021; and by the Spanish Ministry of Science, Innovation, and Universities RTI2018-100683-B-I00 grant.
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Fernández-Becerra, L., Guerrero-Higueras, Á.M., Rodríguez-Lera, F.J., Fernández-Llamas, C. (2022). Analysis of the Performance of Different Accountability Strategies for Autonomous Robots. In: Gude Prego, J.J., de la Puerta, J.G., García Bringas, P., Quintián, H., Corchado, E. (eds) 14th International Conference on Computational Intelligence in Security for Information Systems and 12th International Conference on European Transnational Educational (CISIS 2021 and ICEUTE 2021). CISIS - ICEUTE 2021. Advances in Intelligent Systems and Computing, vol 1400. Springer, Cham. https://doi.org/10.1007/978-3-030-87872-6_5
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