Stina Klein
ABSTRACT
Solving failures is part of our private and work lives. With the ongoing changes in the industrial production setting, we have to deal with new failure originators: collaborative robots (cobots). Failure communication and subsequent recovery are essential to improve performance and restore trust after cobot failures. Therefore, we propose a framework for cobot failure management (FCFM) to support failure communication and solving in the production context. In a study with workers (N = 35), we investigate the impact of the helpfulness of the FCFM for workers. The first preliminary results demonstrate that the FCFM helps facilitate failure communication and rectification.
- Muhammad Awais and Dominik Henrich. 2012. Proactive premature intention estimation for intuitive human-robot collaboration. In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, Vilamoura-Algarve, Portugal, 4098--4103. https://doi.org/10.1109/IROS.2012.6385880Google Scholar
Cross Ref
- Jimmy Baraglia, Maya Cakmak, Yukie Nagai, Rajesh Rao, and Minoru Asada. 2016. Initiative in robot assistance during collaborative task execution. In 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, Christchurch, New Zealand, 67--74. https://doi.org/10.1109/HRI.2016.7451735Google ScholarCross Ref
- Jenay M Beer, Arthur D Fisk, and Wendy A Rogers. 2014. Toward a Framework for Levels of Robot Autonomy in Human-Robot Interaction. Journal of Human-Robot Interaction, Vol. 3, 2 (June 2014), 74. https://doi.org/10.5898/JHRI.3.2.BeerGoogle ScholarDigital Library
- Martin Buss, Daniel Carton, Barbara Gonsior, Kolja Kuehnlenz, Christian Landsiedel, Nikos Mitsou, Roderick de Nijs, Jakub Zlotowski, Stefan Sosnowski, Ewald Strasser, Manfred Tscheligi, Astrid Weiss, and Dirk Wollherr. 2011. Towards proactive human-robot interaction in human environments. In 2011 2nd International Conference on Cognitive Infocommunications (CogInfoCom). 1--6.Google Scholar
- George Charalambous, Sarah Fletcher, and Philip Webb. 2016. The Development of a Scale to Evaluate Trust in Industrial Human-robot Collaboration. International Journal of Social Robotics, Vol. 8, 2 (April 2016), 193--209. https://doi.org/10.1007/s12369-015-0333--8Google ScholarCross Ref
- Munjal Desai, Poornima Kaniarasu, Mikhail Medvedev, Aaron Steinfeld, and Holly Yanco. 2013. Impact of robot failures and feedback on real-time trust. In 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, 251--258. https://doi.org/10.1109/HRI.2013.6483596Google ScholarCross Ref
- Anais Garrell, Michael Villamizar, Francesc Moreno-Noguer, and Alberto Sanfeliu. 2017. Teaching Robot's Proactive Behavior Using Human Assistance. International Journal of Social Robotics, Vol. 9, 2 (April 2017), 231--249. https://doi.org/10.1007/s12369-016-0389-0Google ScholarCross Ref
- Manuel Giuliani, Nicole Mirnig, Gerald Stollnberger, Susanne Stadler, Roland Buchner, and Manfred Tscheligi. 2015. Systematic analysis of video data from different human--robot interaction studies: a categorization of social signals during error situations. Frontiers in Psychology, Vol. 6 (2015). https://www.frontiersin.org/articles/10.3389/fpsyg.2015.00931Google ScholarCross Ref
- Jasmin Grosinger, Federico Pecora, and Alessandro Saffiotti. 2016. Making Robots Proactive through Equilibrium Maintenance. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI'16). AAAI Press, 3375--3381. event-place: New York, New York, USA.Google ScholarDigital Library
- Adriana Hamacher, Nadia Bianchi-Berthouze, Anthony G. Pipe, and Kerstin Eder. 2016. Believing in BERT: Using expressive communication to enhance trust and counteract operational error in physical Human-robot interaction. In 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). 493--500. https://doi.org/10.1109/ROMAN.2016.7745163Google ScholarDigital Library
- Peter A. Hancock, Deborah R. Billings, Kristin E. Schaefer, Jessie Y. C. Chen, Ewart J. de Visser, and Raja Parasuraman. 2011. A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction. Human Factors, Vol. 53, 5 (Oct. 2011), 517--527. https://doi.org/10.1177/0018720811417254 Publisher: SAGE Publications Inc.Google ScholarCross Ref
- Sandra G. Hart and Lowell E. Staveland. 1988. Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. In Advances in Psychology. Vol. 52. Elsevier, 139--183. https://doi.org/10.1016/S0166--4115(08)62386--9Google ScholarCross Ref
- Shanee Honig and Tal Oron-Gilad. 2018. Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development. Frontiers in Psychology, Vol. 9 (2018). https://www.frontiersin.org/articles/10.3389/fpsyg.2018.00861Google ScholarCross Ref
- Chien-Ming Huang and Bilge Mutlu. 2016. Anticipatory robot control for efficient human-robot collaboration. In 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI). 83--90. https://doi.org/10.1109/HRI.2016.7451737 ISSN: 2167--2148.Google ScholarCross Ref
- Jiun-Yin Jian, Ann M. Bisantz, and Colin G. Drury. 2000. Foundations for an Empirically Determined Scale of Trust in Automated Systems. International Journal of Cognitive Ergonomics, Vol. 4, 1 (March 2000), 53--71. https://doi.org/10.1207/S15327566IJCE0401_04Google ScholarCross Ref
- Yusuke Kato, Takayuki Kanda, and Hiroshi Ishiguro. 2015. May I help you?: Design of Human-like Polite Approaching Behavior. In Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction. ACM, Portland Oregon USA, 35--42. https://doi.org/10.1145/2696454.2696463Google ScholarDigital Library
- Matthias Kraus, Nicolas Wagner, Zoraida Callejas, and Wolfgang Minker. 2021b. The Role of Trust in Proactive Conversational Assistants. IEEE Access, Vol. 9 (2021), 112821--112836. https://doi.org/10.1109/ACCESS.2021.3103893Google ScholarCross Ref
- Matthias Kraus, Nicolas Wagner, and Wolfgang Minker. 2020. Effects of Proactive Dialogue Strategies on Human-Computer Trust. In Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization. ACM, Genoa Italy, 107--116. https://doi.org/10.1145/3340631.3394840Google ScholarDigital Library
- Matthias Kraus, Nicolas Wagner, and Wolfgang Minker. 2021a. Modelling and Predicting Trust for Developing Proactive Dialogue Strategies in Mixed-Initiative Interaction. In Proceedings of the 2021 International Conference on Multimodal Interaction. ACM, Montréal QC Canada, 131--140. https://doi.org/10.1145/3462244.3479906Google ScholarDigital Library
- Matthias Kraus, Nicolas Wagner, Ron Riekenbrauck, and Wolfgang Minker. 2023. Improving Proactive Dialog Agents Using Socially-Aware Reinforcement Learning. In Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization. ACM, Limassol Cyprus, 146--155. https://doi.org/10.1145/3565472.3595611Google ScholarDigital Library
- Matthias Kraus, Nicolas Wagner, Nico Untereiner, and Wolfgang Minker. 2022. Including Social Expectations for Trustworthy Proactive Human-Robot Dialogue. In Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization. ACM, Barcelona Spain, 23--33. https://doi.org/10.1145/3503252.3531294Google ScholarDigital Library
- Woo Young Kwon and Il Hong Suh. 2014. Planning of proactive behaviors for human--robot cooperative tasks under uncertainty. Knowledge-Based Systems, Vol. 72 (Dec. 2014), 81--95. https://doi.org/10.1016/j.knosys.2014.08.021Google ScholarDigital Library
- Phoebe Liu, Dylan F. Glas, Takayuki Kanda, and Hiroshi Ishiguro. 2018. Learning proactive behavior for interactive social robots. Autonomous Robots, Vol. 42, 5 (June 2018), 1067--1085. https://doi.org/10.1007/s10514-017--9671--8Google ScholarDigital Library
- Zhenhui Peng, Yunhwan Kwon, Jiaan Lu, Ziming Wu, and Xiaojuan Ma. 2019. Design and Evaluation of Service Robot's Proactivity in Decision-Making Support Process. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, Glasgow Scotland Uk, 1--13. https://doi.org/10.1145/3290605.3300328Google ScholarDigital Library
- Maia Stiber and Chien-Ming Huang. 2021. Not All Errors Are Created Equal: Exploring Human Responses to Robot Errors with Varying Severity. In Companion Publication of the 2020 International Conference on Multimodal Interaction (ICMI '20 Companion ). Association for Computing Machinery, New York, NY, USA, 97--101. https://doi.org/10.1145/3395035.3425245Google ScholarDigital Library
- Fabio A. Storm, Mattia Chiappini, Carla Dei, Caterina Piazza, Elisabeth André, Nadine Reißner, Ingrid Brdar, Antonella Delle Fave, Patrick Gebhard, Matteo Malosio, Alberto Peña Fernández, Gianluigi Reni. 2022. Physical and mental well-being of cobot workers: A scoping review using the Software-Hardware?Environment?Liveware?Liveware?Organization model. Human Factors and Ergonomics in Manufacturing & Service Industries, Vol. 32, 5 (Sept. 2022), 419--435. https://doi.org/10.1002/hfm.20952Google ScholarCross Ref
- Alexandra Weidemann and Nele Rußwinkel. 2021. The Role of Frustration in Human--Robot Interaction -- What Is Needed for a Successful Collaboration? Frontiers in Psychology, Vol. 12 (2021). https://www.frontiersin.org/articles/10.3389/fpsyg.2021.640186Google ScholarCross Ref
- Michael S Wogalter. 2018. Communication-human information processing (C-HIP) model. In Forensic Human Factors and Ergonomics. CRC Press, 33--49.Google Scholar
- Zhang, Yu, Vignesh Narayanan, Tathagata Chakraborti, and Subbarao Kambhampati. 2015. A human factors analysis of proactive support in human-robot teaming. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, Hamburg, Germany, 3586--3593. https://doi.org/10.1109/IROS.2015.7353878Google ScholarDigital Library
Index Terms
- Creating a Framework for a User-Friendly Cobot Failure Management in Human-Robot Collaboration
Recommendations
Reactive Planning on a Collaborative Robot for Industrial Applications
ICINCO 2015: Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2A challenge for roboticists consist in promoting collaborative robotics for industrial applications, i.e. allowing
robots to be used close to humans, without barriers. Safety becomes the key issue. For manipulation tasks, a
part of the problem is solved ...
Autonomous Air-Hockey Playing Cobot Using Optimal Control and Vision-Based Bayesian Tracking
Towards Autonomous Robotic SystemsAbstractThis paper presents a novel autonomous air-hockey playing collaborative robot (cobot) that provides human-like gameplay against human opponents. Vision-based Bayesian tracking of the puck and striker are used in an Analytic Hierarchy Process (AHP)-...
A Distributed Fuzzy-Based Failure Management for Wireless Sensor Networks
CTRQ '09: Proceedings of the 2009 Second International Conference on Communication Theory, Reliability, and Quality of ServiceIn addition to limited energy resources in wireless sensor networks, failure of the nodes is a constraint to provide a reliable communication. As the failure of a node may have many reasons like mobility of the node and node or link failure, it is clear ...
Comments