Probabilistic modelling and safety assurance of an agriculture robot providing light-treatment

Mustafa Adam, Kangfeng Ye, David A. Anisi, Ana Cavalcanti, Jim Woodcock, Robert Morris

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Continued adoption of agricultural robots postulates the farmer’s trust in the reliability, robustness and safety of the new technology. This motivates our work on safety assurance of agricultural robots, particularly their ability to detect, track and avoid obstacles and humans. This paper considers a probabilistic modelling and risk analysis framework for use in the early development phases. Starting off
with hazard identification and a risk assessment matrix, the behaviour of the mobile robot platform, sensor and perception system, and any humans present are captured using three state machines. An auto-generated probabilistic model is then solved and analysed using the probabilistic model checker PRISM. The result provides unique insight into fundamental development and engineering aspects by quantifying the effect of the risk mitigation actions and risk reduction associated with distinct design concepts. These include implications of adopting
a higher performance and more expensive Object Detection System or opting for a more elaborate warning system to increase human awareness. Although this paper mainly focuses on the initial concept-development phase, the proposed safety-assurance framework can also be used during implementation, and subsequent deployment and operation phases.
Original languageEnglish
Title of host publication2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
Number of pages7
ISBN (Electronic)979-8-3503-2069-5
ISBN (Print)979-8-3503-2070-1
Publication statusPublished - 28 Sept 2023
Event19th IEEE International Conference on Automation Science and Engineering, CASE 2023 - Auckland, New Zealand
Duration: 26 Aug 202330 Aug 2023

Publication series

NameIEEE International Conference on Automation Science and Engineering
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089


Conference19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Country/TerritoryNew Zealand

Bibliographical note

Funding Information:
The authors would like to gratefully acknowledge all guidance and fruitful discussions provided by Robert Morris on the hazard and safety aspects of agricultural robots. The research presented in this paper has received partial funding from the Norwegian Research Council (RCN) Robo-Farmer, project number 336712, the UK EPSRC Grants EP/M025756/1, EP/R025479/1, and EP/V026801/2, and the Royal Academy of Engineering Grant No CiET1718/45.

Publisher Copyright:
© 2023 IEEE.

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