Qualitative vision-based navigation based on sloped funnel lane concept
Mohamad Mahdi Kassir, Maziar Palhang, Mohammad Reza Ahmadzadeh

TL;DR
This paper introduces the sloped funnel lane, an improved visual navigation method that incorporates roll and pitch angles to enhance maneuverability and robustness in robot path following without requiring camera calibration.
Contribution
The paper proposes a novel sloped funnel lane technique that addresses limitations of traditional funnel lane by enabling variable turning radii and reducing translation-rotation ambiguity.
Findings
Effective in complex scenarios on real robots
Improves maneuverability and path accuracy
Reduces path deviation and ambiguity
Abstract
Funnel lane concept is a qualitative visual navigation method which helps robots to autonomously navigate by using a recorded video. A visual path is extracted from the video by extracting some keyframes from the video. The robot uses this visual path for its navigation. Funnel lane unlike some other methods does not make use of traditional calculations of Jacobians, homographies, fundamental matrices, or the focus of expansion, and does not require any camera calibration. However, funnel lane has some shortcomings. One problem is that funnel lane gives no information about the radius of rotation, so in turnings, the robot turns by a constant radius of rotation along the path. This reduces the maneuverability and limits the robot from dealing with all turnings conditions. In addition, this problem makes the robot faces a serious problem in correcting its path when it deviates from the…
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