Increasing safety by combining multiple declarative rules in robotic perception systems

Johann Thor Mogensen Ingibergsson, Dirk Kraft, Ulrik Pagh Schultz*

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Resumé

Advanced cyber-physical systems such as mobile, networked robots are increasingly finding use in everyday society. A critical aspect of mobile robotics is the ability to react to a dynamically changing environment, which imposes significant requirements on the robot perception system. The perception system is key to maintaining safe navigation and operation for the robot and is often considered a safety-critical aspect of the system as a whole. To allow the system to operate in a public area the perception system thus has to be certified. The key issue that we address is how to have safety-compliant systems while keeping implementation transparency high and complexity low. In this paper we present an evaluation of different methods for modelling combinations of simple explicit computer vision rules designed to increase the trustworthiness of the perception system. We utilise the best-performing method, focusing on keeping the models of the perception pipeline transparent and understandable. We find that it is possible to improve the safety of the system with some performance cost, depending on the acceptable risk level.

OriginalsprogEngelsk
TitelCyber Physical Systems. Design, Modeling, and Evaluation : 7th International Workshop, CyPhy 2017, Revised Selected Papers
RedaktørerRoger Chamberlain, Walid Taha, Martin Törngren
ForlagSpringer VS
Publikationsdato13. apr. 2019
Sider43-60
ISBN (Trykt)9783030179090
ISBN (Elektronisk)978-3-030-17910-6
DOI
StatusUdgivet - 13. apr. 2019
Begivenhed7th International Workshop on Design, Modeling, and Evaluation of Cyber Physical Systems, CyPhy 2017 - Seoul, Sydkorea
Varighed: 15. okt. 201720. okt. 2017

Konference

Konference7th International Workshop on Design, Modeling, and Evaluation of Cyber Physical Systems, CyPhy 2017
LandSydkorea
BySeoul
Periode15/10/201720/10/2017
NavnLecture Notes in Computer Science
Vol/bind11267
ISSN0302-9743

Fingeraftryk

Robotics
Robots
Transparency
Computer vision
Navigation
Pipelines
Costs
Cyber Physical System

Citer dette

Ingibergsson, J. T. M., Kraft, D., & Schultz, U. P. (2019). Increasing safety by combining multiple declarative rules in robotic perception systems. I R. Chamberlain, W. Taha, & M. Törngren (red.), Cyber Physical Systems. Design, Modeling, and Evaluation: 7th International Workshop, CyPhy 2017, Revised Selected Papers (s. 43-60). Springer VS. Lecture Notes in Computer Science, Bind. 11267 https://doi.org/10.1007/978-3-030-17910-6_4
Ingibergsson, Johann Thor Mogensen ; Kraft, Dirk ; Schultz, Ulrik Pagh. / Increasing safety by combining multiple declarative rules in robotic perception systems. Cyber Physical Systems. Design, Modeling, and Evaluation: 7th International Workshop, CyPhy 2017, Revised Selected Papers. red. / Roger Chamberlain ; Walid Taha ; Martin Törngren. Springer VS, 2019. s. 43-60 (Lecture Notes in Computer Science, Bind 11267).
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Ingibergsson, JTM, Kraft, D & Schultz, UP 2019, Increasing safety by combining multiple declarative rules in robotic perception systems. i R Chamberlain, W Taha & M Törngren (red), Cyber Physical Systems. Design, Modeling, and Evaluation: 7th International Workshop, CyPhy 2017, Revised Selected Papers. Springer VS, Lecture Notes in Computer Science, bind 11267, s. 43-60, 7th International Workshop on Design, Modeling, and Evaluation of Cyber Physical Systems, CyPhy 2017, Seoul, Sydkorea, 15/10/2017. https://doi.org/10.1007/978-3-030-17910-6_4

Increasing safety by combining multiple declarative rules in robotic perception systems. / Ingibergsson, Johann Thor Mogensen; Kraft, Dirk; Schultz, Ulrik Pagh.

Cyber Physical Systems. Design, Modeling, and Evaluation: 7th International Workshop, CyPhy 2017, Revised Selected Papers. red. / Roger Chamberlain; Walid Taha; Martin Törngren. Springer VS, 2019. s. 43-60 (Lecture Notes in Computer Science, Bind 11267).

Publikation: Bidrag til bog/antologi/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

TY - GEN

T1 - Increasing safety by combining multiple declarative rules in robotic perception systems

AU - Ingibergsson, Johann Thor Mogensen

AU - Kraft, Dirk

AU - Schultz, Ulrik Pagh

PY - 2019/4/13

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N2 - Advanced cyber-physical systems such as mobile, networked robots are increasingly finding use in everyday society. A critical aspect of mobile robotics is the ability to react to a dynamically changing environment, which imposes significant requirements on the robot perception system. The perception system is key to maintaining safe navigation and operation for the robot and is often considered a safety-critical aspect of the system as a whole. To allow the system to operate in a public area the perception system thus has to be certified. The key issue that we address is how to have safety-compliant systems while keeping implementation transparency high and complexity low. In this paper we present an evaluation of different methods for modelling combinations of simple explicit computer vision rules designed to increase the trustworthiness of the perception system. We utilise the best-performing method, focusing on keeping the models of the perception pipeline transparent and understandable. We find that it is possible to improve the safety of the system with some performance cost, depending on the acceptable risk level.

AB - Advanced cyber-physical systems such as mobile, networked robots are increasingly finding use in everyday society. A critical aspect of mobile robotics is the ability to react to a dynamically changing environment, which imposes significant requirements on the robot perception system. The perception system is key to maintaining safe navigation and operation for the robot and is often considered a safety-critical aspect of the system as a whole. To allow the system to operate in a public area the perception system thus has to be certified. The key issue that we address is how to have safety-compliant systems while keeping implementation transparency high and complexity low. In this paper we present an evaluation of different methods for modelling combinations of simple explicit computer vision rules designed to increase the trustworthiness of the perception system. We utilise the best-performing method, focusing on keeping the models of the perception pipeline transparent and understandable. We find that it is possible to improve the safety of the system with some performance cost, depending on the acceptable risk level.

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Ingibergsson JTM, Kraft D, Schultz UP. Increasing safety by combining multiple declarative rules in robotic perception systems. I Chamberlain R, Taha W, Törngren M, red., Cyber Physical Systems. Design, Modeling, and Evaluation: 7th International Workshop, CyPhy 2017, Revised Selected Papers. Springer VS. 2019. s. 43-60. (Lecture Notes in Computer Science, Bind 11267). https://doi.org/10.1007/978-3-030-17910-6_4