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- W2292594239 abstract "Most of the modern, advanced obstacle avoidance systems for ground vehicles are rather complicated and expensive, and cannot be directly applied to the complex autonomous bicycle problem. With this paper we introduce a novel and minimal design and implementation approach for a single laser range sensor (LRS)-based obstacle avoidance and road surface quality detection system, specifically created for use on-board an autonomous bicycle and mainly inspired from the human riding behavior. The system utilizes the measurements from the mounted LRS to detect dynamic obstacles that lie inside the bicycle's immediate environment and avoid the ones with paths intersecting its own. The LRS's mechanical base and rotating mechanism were specially designed to fit the lightweight structure of the bicycle and a specific rotation pattern on the sagittal plane of the bicycle was created to maximize sensing efficiency, resembling the way humans combine information from one glance. The RANSAC Line Detection algorithm is used to identify the ground surface line, evaluate the road surface quality and detect bumps or holes on the bicycle path in order to avoid them. Our experimental results show promising bicycle behavior and reliable obstacle avoidance in both indoor and outdoor environments at different speeds." @default.
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- W2292594239 date "2015-12-01" @default.
- W2292594239 modified "2023-09-25" @default.
- W2292594239 title "Human behavior inspired obstacle avoidance & road surface quality detection for autonomous bicycles" @default.
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- W2292594239 doi "https://doi.org/10.1109/robio.2015.7419087" @default.
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