Abstract
Consider the definition of the technical state of the mobile robot using test and diagnostic tools. The analysis determined the interaction between the object of diagnosis, control and diagnostic tools. Since this interaction is the process of applying for facility diagnosis of multiple actions (outputs) and multiple-shift analysis and responses (outputs) to these actions. Actions for mobile robot may come from control and diagnostic agents or external (on the system of diagnosis) signals defined working algorithm of the object. Depending on the mode of operation of differentiated functional system test and diagnosis. Summarizes the functional diagrams of these systems. The use of functional diagnosis system to verify proper operation and troubleshooting the most critical equipment, assemblies and systems mobile robot that violate normal functioning. From this we can conclude that these systems work when the mobile robot is used for other purposes. They can be used in simulation mode operation work. In this case, should be provided simulation workflows. Such use of functional diagnosis should be used during debugging and repair system. Revealed that the development of diagnostic systems for interaction between object and vehicle diagnostics to be resolved following tasks: feasibility selecting the type and purpose of the system diagnostics; analysis of the physical processes occurring in the facility diagnosis.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wooldridge, M.J., Jennings, N.R.: Intelligent agents: theory and practice. Knowl. Eng. Rev. 10(2), 115–152 (1995)
Zambonelli, F., Jennings, N.R., Wooldridge, M.J.: Developing multiagent systems: the gaia methodology. ACM Trans. Softw. Eng. Method. 12(3), 317–370 (2003)
Zambonelli, F., Omicini, A.: Challenges and research directions in agent-oriented software engineering. J. Auton. Agents Multiagent Syst. 9(3), 253–283 (2004)
Korobiichuk, I.: Mathematical model of precision sensor for an automatic weapons stabilizer system. Measurement 89, 151–158 (2016). doi:10.1016/j.measurement.2016.04.017
Korobiichuk, I., Bezvesilna, O., Ilchenko, A., Shadura, V., Nowicki, M., Szewczyk, R.: A mathematical model of the thermo-anemometric flowmeter. Sensors 15, 22899–22913 (2015). doi:10.3390/s150922899
Korobiichuk, I., Podchashinskiy, Y., Shapovalova, O., Shadura, V., Nowicki, M., Szewczyk, R.: Precision increase in automated digital image measurement systems of geometric values. In: Jabłoński, R., Brezina, T. (eds.) Advanced Mechatronics Solutions. AISC, vol. 393, pp. 335–340. Springer, Heidelberg (2016). doi:10.1007/978-3-319-23923-1_51
Shushlyapin, S.V.: Measure the accuracy and reliability of the diagnosis units tractor transmission. Tractor power in crop production, – Coll, scientific. tr. HGTUSKH, Vol. 5, 135–140 (2002)
Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press (1995)
Dianov, V.N.: Avtomatika i telemekhanika [Automation and telemechanics], no. 7, pp. 119–138 (2012)
Talanchuk, P.M., Golubkov, S.P., Maslov, V.P., et al.: Sensory v kontrol’no izmeritel’noy tekhnike [Sensors in inspection technologies], 173 p. Tekhnika, Kiev (1991)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Marchenkova, S. (2017). Diagnostic Systems of Mobile Robot Technical State. In: Szewczyk, R., Kaliczyńska, M. (eds) Recent Advances in Systems, Control and Information Technology. SCIT 2016. Advances in Intelligent Systems and Computing, vol 543. Springer, Cham. https://doi.org/10.1007/978-3-319-48923-0_34
Download citation
DOI: https://doi.org/10.1007/978-3-319-48923-0_34
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-48922-3
Online ISBN: 978-3-319-48923-0
eBook Packages: EngineeringEngineering (R0)