Abstract
Accurate autonomous navigation for off-terrain utility vehicles with no human intervention is an essential requirement to achieve full automation. Within several applications, though higher autonomous navigational accuracy (almost ±2.5 cm) has been achieved in some commercially available vehicles yet requirements for human intervention is still very much required in several situations. This study investigates autonomous navigational accuracy of PurePursuit algorithm for different reference points for a non-steerable-wheels center-steered articulated vehicle. PurePursuit algorithm is preferable choice for path tracking for its simplicity and for vehicles where high speed is not a requirement. Evaluation of PurePursuit algorithm for utility vehicles of type studied in this paper is somewhat less explored area. We have compared the autonomous navigational accuracy of PurePursuit algorithm for different reference points for a set of different path complexities that also includes vehicles kinematic constraints in simulation environment. Average lateral and heading deviations were calculated for a set of different path complexities, and it was found that in general proposed reference point for PurePursuit algorithm for center-steer articulated vehicle shows better lateral and heading autonomous navigational accuracy than the traditional PurePursuit algorithm.
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This work was funded by The Royal Swedish Agricultural Academy (SLO-foundation).
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Latif, S., Lindbäck, T., Karlberg, M. (2023). Evaluation of Autonomous Navigational Accuracy for Different Reference Points in PurePursuit Algorithm for Center-Steered Articulated Vehicles. In: Jo, J., et al. Robot Intelligence Technology and Applications 7. RiTA 2022. Lecture Notes in Networks and Systems, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-031-26889-2_18
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