2020
DOI: 10.21203/rs.3.rs-54747/v1
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Improving Lateral Safety Distance-Based on Feature Detection and Probabilistic Roadmaps for Unmanned Vehicle Path Planning

Abstract: Most of the existing path-planning algorithms do not consider lateral safe distance requirements in practical applications. Hence, in this study, a new path point selection algorithm is proposed for path planning. The algorithm first used the Harris and Line Segment Detector(LSD) algorithms to detect and obtain the corner and edge information of obstacles. A vertical line was provided to the edge of the surrounding obstacles along each corner successively. In this process, the narrow impassable area in the map… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2021
2021

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 20 publications
0
1
0
Order By: Relevance
“…Despite the advantages presented, path generation through PRM-based probabilistic exploration presents the drawback that the paths generated tend to present a Zig-Zag pattern that can affect the flight dynamics of UAVs [27,28]. For this reason, the implemented path planner combines, in a final phase, with a path smoothing algorithm responsible for removing unnecessary path points, thus improving the pattern of the paths, favoring the achievement of long stretches of straight lines and, in addition, optimizing the total distance traveled by the swarm and, with it, response times and efficiency when completing a mission.…”
Section: Layer Ii: Smoothing Trajectoriesmentioning
confidence: 99%
“…Despite the advantages presented, path generation through PRM-based probabilistic exploration presents the drawback that the paths generated tend to present a Zig-Zag pattern that can affect the flight dynamics of UAVs [27,28]. For this reason, the implemented path planner combines, in a final phase, with a path smoothing algorithm responsible for removing unnecessary path points, thus improving the pattern of the paths, favoring the achievement of long stretches of straight lines and, in addition, optimizing the total distance traveled by the swarm and, with it, response times and efficiency when completing a mission.…”
Section: Layer Ii: Smoothing Trajectoriesmentioning
confidence: 99%