Specification, stochastic modeling and analysis of interactive service robotic applications
Assistive robotic systems are quickly becoming a core technology for the service sector as they are understood capable of supporting people in need of assistance in a wide variety of tasks. This step poses a number of ethical and technological questions. The research community is wondering how servi...
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| Vydáno v: | Robotics and autonomous systems Ročník 163; s. 104387 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.05.2023
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| Témata: | |
| ISSN: | 0921-8890, 1872-793X |
| On-line přístup: | Získat plný text |
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| Abstract | Assistive robotic systems are quickly becoming a core technology for the service sector as they are understood capable of supporting people in need of assistance in a wide variety of tasks. This step poses a number of ethical and technological questions. The research community is wondering how service robotics can be a step forward in human care and aid, and how robotics applications can be realized in order to put the human role at the forefront. Therefore, there is a growing demand for frameworks supporting robotic application designers in a “human-aware” development process. This paper presents a model-driven framework for analyzing and developing human–robot interactive scenarios in non-industrial settings with significant sources of uncertainty. The framework’s core is a formal model of the agents at play – the humans and the robot – and the robot’s mission, which is then put through verification to estimate the probability of completing the mission. The model captures non-trivial features related to human behavior, specifically the unpredictability of human choices and physiological aspects tied to their state of health. To foster the framework’s accessibility, we present a verification tool-agnostic Domain-Specific Language that allows designers lacking expertise in formal modeling to configure the interactive scenarios in a user-friendly manner. We compare the formal analysis outputs with results obtained by deploying benchmark scenarios in the physical environment with a real mobile robot to assess whether the formal model adheres to reality and whether the verification results are accurate. The entire development pipeline is then tested on several scenarios from the healthcare setting to assess its flexibility and effectiveness in the application design process.
•Design of scenarios where robots and humans interact closely.•Model-driven framework to design, deploy, and reconfigure scenarios.•Extensive coverage of realistic healthcare use cases.•Reliable estimations of quality metrics of the scenario. |
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| AbstractList | Assistive robotic systems are quickly becoming a core technology for the service sector as they are understood capable of supporting people in need of assistance in a wide variety of tasks. This step poses a number of ethical and technological questions. The research community is wondering how service robotics can be a step forward in human care and aid, and how robotics applications can be realized in order to put the human role at the forefront. Therefore, there is a growing demand for frameworks supporting robotic application designers in a “human-aware” development process. This paper presents a model-driven framework for analyzing and developing human–robot interactive scenarios in non-industrial settings with significant sources of uncertainty. The framework’s core is a formal model of the agents at play – the humans and the robot – and the robot’s mission, which is then put through verification to estimate the probability of completing the mission. The model captures non-trivial features related to human behavior, specifically the unpredictability of human choices and physiological aspects tied to their state of health. To foster the framework’s accessibility, we present a verification tool-agnostic Domain-Specific Language that allows designers lacking expertise in formal modeling to configure the interactive scenarios in a user-friendly manner. We compare the formal analysis outputs with results obtained by deploying benchmark scenarios in the physical environment with a real mobile robot to assess whether the formal model adheres to reality and whether the verification results are accurate. The entire development pipeline is then tested on several scenarios from the healthcare setting to assess its flexibility and effectiveness in the application design process.
•Design of scenarios where robots and humans interact closely.•Model-driven framework to design, deploy, and reconfigure scenarios.•Extensive coverage of realistic healthcare use cases.•Reliable estimations of quality metrics of the scenario. |
| ArticleNumber | 104387 |
| Author | Lestingi, Livia Bersani, Marcello M. Zerla, Davide Rossi, Matteo |
| Author_xml | – sequence: 1 givenname: Livia orcidid: 0000-0001-8724-1541 surname: Lestingi fullname: Lestingi, Livia email: livia.lestingi@polimi.it organization: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Ponzio 34/5, 20133 Milan, Italy – sequence: 2 givenname: Davide surname: Zerla fullname: Zerla, Davide email: davide.zerla@mail.polimi.it organization: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Ponzio 34/5, 20133 Milan, Italy – sequence: 3 givenname: Marcello M. surname: Bersani fullname: Bersani, Marcello M. email: marcellomaria.bersani@polimi.it organization: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Ponzio 34/5, 20133 Milan, Italy – sequence: 4 givenname: Matteo surname: Rossi fullname: Rossi, Matteo email: matteo.rossi@polimi.it organization: Dipartimento di Meccanica, Politecnico di Milano, Via Privata Giuseppe La Masa 1, 20156 Milan, Italy |
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| Cites_doi | 10.1016/j.rcim.2019.01.001 10.1109/70.370506 10.3182/20110828-6-IT-1002.03022 10.1016/0304-3975(94)00202-T 10.1109/ACCESS.2021.3117852 10.1007/s00165-020-00509-0 10.1016/j.techfore.2016.08.019 10.1093/biomet/26.4.404 10.1177/0278364919883338 10.1016/j.robot.2018.10.009 10.1109/ACCESS.2016.2613642 10.1016/j.proeng.2011.08.492 10.1002/mus.10014 10.1145/3158668 10.1007/s100090050010 10.1109/TRO.2019.2937471 10.1080/00140139.2017.1416180 10.1016/1050-6411(91)90023-X 10.1007/BF02590638 10.1371/journal.pone.0162034 10.1007/s10009-014-0361-y 10.1016/S0006-3495(02)75580-X 10.1177/0278364913481635 10.1007/s12369-017-0431-x 10.1109/ACCESS.2020.2970143 10.1109/MRA.2011.942116 10.1145/227595.227602 10.1109/TSE.2019.2945329 10.1016/j.apm.2015.03.038 10.1007/s10270-018-00710-z 10.1109/32.588521 10.1152/jappl.1977.43.4.750 10.1145/3466819 |
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| Keywords | Formal methods for robotics Model-driven engineering Domain-specific languages for robotics Stochastic hybrid automata Statistical model-checking Models of human behavior Service robotics Human–robot interaction |
| Language | English |
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