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Monitored Neural Networks for Autonomous Articulated Machines
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.
2020 (English)Independent thesis Advanced level (degree of Master (Two Years)), 300 HE creditsStudent thesisAlternative title
Monitored Neural Network for Curvature Steering of Autonomous Articulated Machines (English)
Abstract [en]

Being able to safely control autonomous heavy machinery is of uttermost importance for the conversion of traditional machines to autonomous machines. With the continuous growth of autonomous vehicles around the globe, an increasing effort has been put into certifying autonomous vehicles in terms of reliability and safety. In this thesis, we will investigate the problem with a deviation from the planned path for an autonomous hauler from Volvo Construction Equipment. The autonomous hauler has an error within the kinematic model, the feed-forward curvature-steering controller, due to a slip-effect that comes with the third wheel-axle. The deviation can especially be seen in sharp curves, where the deviation needs to be decreased in order to make the autonomous hauler more dependable and achieve an increased accuracy when following any given path. The aim of the thesis is to develop a fully functional Artificial Neural Network that has a new steering angle as output. The hypothesis for this thesis is to use an ANN to mimic the steering of a human driver, since a real driver compensates for the slipping behavior; both because the operator knows where on the road the machine is and also in the way that a human thinks many steps ahead whilst driving. This proposed ANN will have a monitor function which ensures that the steering angle command operates within its boundaries. Hence this thesis implies that it is indeed possible to ensure that the ANN performs reliably with the help of a monitor function in a simulated environment and can thus be used in dependable systems.

Place, publisher, year, edition, pages
2020. , p. 49
Keywords [en]
Slip, ANN, Neural Networks, Hauler, Monitored Neural Networks, Verification Neural Networks, Curvature Steering, Autonomous machines, Articulated Machines, Volvo CE, side-slip, slip error, Reliable Neural Networks, Dependable Neural Networks
National Category
Reliability and Maintenance Robotics Control Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-48708OAI: oai:DiVA.org:mdh-48708DiVA, id: diva2:1440033
External cooperation
Volvo Construction Equipment
Subject / course
Miscellaneous
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Examiners
Available from: 2020-06-16 Created: 2020-06-12 Last updated: 2020-06-16Bibliographically approved

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CiteExportLink to record
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  • apa
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