Towards Safe Human-Robot Interaction

Grigore, Elena Corina; Eder, Kerstin; Lenz, Alexander; Skachek, Sergey; Pipe, Anthony G.; Melhuish, Chris

doi:10.1007/978-3-642-23232-9_29

Cited by 7 publications

(6 citation statements)

References 4 publications

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“…For example, Wosch et al [36] showed an efficient motion planner that guaranteed safe motions of a robot bartender that worked closely with humans; Masuda and Misaki [19] presented "T-Bartender," a robot that was able to serve green tea in a traditional Japanese way; Limbu et al [17] implemented "FusionBot," a mobile robot bartender that served drinks in homes; while Grigore et al [15] used a robot bartender as an Figure 2: System architecture example of a human-robot interaction scenario in which the safety of the human could be guaranteed by using verification techniques.…”

Section: Related Workmentioning

confidence: 99%

Comparing task-based and socially intelligent behaviour in a robot bartender

Giuliani

Petrick

Foster

et al. 2013

Proceedings of the 15th ACM on International Conference on Multimodal Interaction

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We address the question of whether service robots that interact with humans in public spaces must express socially appropriate behaviour. To do so, we implemented a robot bartender which is able to take drink orders from humans and serve drinks to them. By using a highlevel automated planner, we explore two different robot interaction styles: in the task only setting, the robot simply fulfils its goal of asking customers for drink orders and serving them drinks; in the socially intelligent setting, the robot additionally acts in a manner socially appropriate to the bartender scenario, based on the behaviour of humans observed in natural bar interactions. The results of a user study show that the interactions with the socially intelligent robot were somewhat more efficient, but the two implemented behaviour settings had only a small influence on the subjective ratings. However, there were objective factors that influenced participant ratings: the overall duration of the interaction had a positive influence on the ratings, while the number of system order requests had a negative influence. We also found a cultural difference: German participants gave the system higher pre-test ratings than participants who interacted in English, although the post-test scores were similar.

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Section: Related Workmentioning

confidence: 99%

Comparing task-based and socially intelligent behaviour in a robot bartender

Giuliani

Petrick

Foster

et al. 2013

Proceedings of the 15th ACM on International Conference on Multimodal Interaction

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“…In the midst of this emphasis on AI technology, Tanaka and Kimura (2010) pointed out that all technologies have strengths and weaknesses, and this makes it imperative for humans to identify the best possible methods to use them [8], while Nadimpalli (2017) stated that physical performance gains are the biggest benefit of AI technology [9]. Regarding the technical aspects of AI technology, Grigore et al (2011) pointed out that robots have been created to enhance the quality of human lives, and stated that these robots are safe and useful [10]. He stressed that in future, technological advances will be required so that robots can provide help and fulfill their duties more safely and skillfully [10].…”

Section: Introductionmentioning

confidence: 99%

Serving Robots: Management and Applications for Restaurant Business Sustainability

Jang

Lee

2020

Sustainability

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This study focuses on the attributes of serving robots, which include “anthropomorphism,” “animacy,” “likeability,” “intelligence,” and “safety,” and their effect on restaurant customers. The study aims to provide a sustainable development model for the restaurant business, which is suffering from a shortage of manpower. The study identifies the relationships among serving robots’ attributes, perceived benefits, perceived risks, perceived value, satisfaction, and revisit intention of customers. An online survey was conducted with customers, aged eighteen years or older, of restaurants that use serving robots. A total of 294 surveys were used for the final analysis. The results indicate that there are statistically significant relationships between “likeability” and perceived benefits, “intelligence” and perceived benefits, “safety” and perceived benefits, and “safety” and perceived risks. It also confirms that perceived benefits have a positive effect on perceived value, and perceived value has a positive effect on satisfaction and revisit intention. Moreover, satisfaction has a positive effect on revisit intention. Based on these findings, several meaningful theoretical and practical implications that can lead to the sustainability of restaurants are presented.

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“…The following requirements were chosen to illustrate our approach, inspired by Grigore et al (2011) and drawing from standards ISO 10218-1:2011 (2011) for industrial robots, ISO 13482:2014 (2014) for personal care robots, and ISO/TS 15066:2016 (2016) for collaborative robots:…”

Section: System Requirementsmentioning

confidence: 99%

“…Finally, a coverage collector gathered statistics on the triggering of the assertion monitors. The simulator code is available online 6 .…”

Section: Simulation-based Testingmentioning

confidence: 99%

A corroborative approach to verification and validation of human–robot teams

Webster

Western

Araiza-Illan

et al. 2019

The International Journal of Robotics Research

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We present an approach for the verification and validation (V&V) of robot assistants in the context of human-robot interactions (HRI), to demonstrate their trustworthiness through corroborative evidence of their safety and functional correctness. Trust in robot assistants will allow them to transition from the laboratory into our everyday lives. Key challenges include the complex and unpredictable nature of the real world in which assistant and service robots operate, the limitations on available V&V techniques when used individually, and the consequent lack of confidence in the V&V results. Our approach, called corroborative V&V, addresses these challenges by combining several different V&V techniques; in this paper we use formal verification (model checking), simulation-based testing, and user validation in experiments with a real robot. We demonstrate our corroborative V&V approach through a handover task, the most critical part of a complex cooperative manufacturing scenario, for which we propose some safety and liveness requirements to verify and validate. We construct formal models, simulations and an experimental test rig for the HRI. To capture requirements we use temporal logic properties, assertion checkers and textual descriptions. This combination of approaches allows V&V of the HRI task at different levels of modelling detail and thoroughness of exploration, thus overcoming the individual limitations of each technique. Should the resulting V&V evidence present discrepancies, an iterative process between the different V&V techniques takes place until corroboration between the V&V techniques is gained from refining and improving the assets (i.e., system and requirement models) to represent the HRI task in a more truthful manner. Therefore, corroborative V&V affords a systematic approach to "'meta-V&V," in which different V&V techniques can be used to corroborate and check one another, increasing the level of certainty in the results of V&V.

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Towards Safe Human-Robot Interaction

Cited by 7 publications

References 4 publications

Comparing task-based and socially intelligent behaviour in a robot bartender

Comparing task-based and socially intelligent behaviour in a robot bartender

Serving Robots: Management and Applications for Restaurant Business Sustainability

A corroborative approach to verification and validation of human–robot teams

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