Perpendicular Parking of Car-Like Robots Allowing a Cusp on the Path

Kim, Jonghoek

doi:10.1109/access.2020.2971250

Cited by 22 publications

(1 citation statement)

References 20 publications

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“…However, geometric approaches may fail to find the path in complex parking situations where the road is narrow due to obstacles near the parking spot. Moreover, their use can be limited due to the assumption that the path contains one forward/backward direction switch [3], [5], [6].…”

Section: Related Workmentioning

confidence: 99%

Continuous-Curvature Target Tree Algorithm for Path Planning in Complex Parking Environments

Kim¹,

Ahn²,

Park³

2022

Preprint

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Rapidly-exploring random tree (RRT) has been applied for autonomous parking due to quickly solving highdimensional motion planning and easily reflecting constraints. However, planning time increases by the low probability of extending toward narrow parking spots without collisions. To reduce the planning time, the target tree algorithm was proposed, substituting a parking goal in RRT with a set (target tree) of backward parking paths. However, it consists of circular and straight paths, and an autonomous vehicle cannot park accurately because of curvature-discontinuity. Moreover, the planning time increases in complex environments; backward paths can be blocked by obstacles. Therefore, this paper introduces the continuous-curvature target tree algorithm for complex parking environments. First, a target tree includes clothoid paths to address such curvature-discontinuity. Second, to reduce the planning time further, a cost function is defined to construct a target tree that considers obstacles. Integrated with optimalvariant RRT and searching for the shortest path among the reached backward paths, the proposed algorithm obtains a nearoptimal path as the sampling time increases. Experiment results in real environments show that the vehicle more accurately parks, and continuous-curvature paths are obtained more quickly and with higher success rates than those acquired with other sampling-based algorithms.

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Section: Related Workmentioning

confidence: 99%

Continuous-Curvature Target Tree Algorithm for Path Planning in Complex Parking Environments

Kim¹,

Ahn²,

Park³

2022

Preprint

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A model predictive control approach for angle tracking of steer‐by‐wire system with nonlinear transmission ratio

Shi

Wei

Xie

et al. 2022

Asian Journal of Control

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Steer‐by‐wire for full self‐driving vehicles requires rapid angle tracking in the process of steering, making steering system stability paramount. This is particularly challenging for steering wheels accurately without handwheel, for which road feedback information is scarce. While much of the research on steer‐by‐wire has focused on improving the stability of vehicle dynamics, comparatively little is known about the angle tracking control of steer‐by‐wire system for full self‐driving vehicle. Here, we discuss a series of studies on the steering dynamics model and nonlinear transmission ratio of steering system that, collectively, design an angle tracking approach of how the model predictive control algorithm steers the front wheels precisely. The designed approach has been downloaded into a steering control unit and tested by some steering cycles in a steering test bench to fully realize angle tracking control of steer‐by‐wire system in practical engineering.

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Visualization of Power Corridor Based on UAV Line Inspection Data

Liu

et al. 2021

Int J Wireless Inf Networks

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Perpendicular Parking of Car-Like Robots Allowing a Cusp on the Path

Cited by 22 publications

References 20 publications

Continuous-Curvature Target Tree Algorithm for Path Planning in Complex Parking Environments

Continuous-Curvature Target Tree Algorithm for Path Planning in Complex Parking Environments

A model predictive control approach for angle tracking of steer‐by‐wire system with nonlinear transmission ratio

Visualization of Power Corridor Based on UAV Line Inspection Data

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