Research on APF-Bi-RRT Algorithm of Adaptive Step Strategy for Robot Path Planning

Yang, JunLin; Guo, Zhongfeng; Liu, Jian; Liu, Siyi

doi:10.1007/s13369-024-09642-x

Arab J Sci Eng

2024

DOI: 10.1007/s13369-024-09642-x

|View full text |Cite

Research on APF-Bi-RRT Algorithm of Adaptive Step Strategy for Robot Path Planning

JunLin Yang,

Zhongfeng Guo,

Jian Liu

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A 3D Path Planning Algorithm for UAVs Based on an Improved Artificial Potential Field and Bidirectional RRT*

Huang,

Li,

Dai

et al. 2024

Drones

View full text Add to dashboard Cite

Efficient and effective path planning can significantly enhance the task execution capabilities of UAVs in complex environments. This paper proposes an improved sampling-based path planning algorithm, Bi-APF-RRT*, which integrates an Artificial Potential Field (APF) method with a newly introduced repulsive coefficient and incorporates dynamic step size adjustments. To further improve path planning performance, the algorithm introduces strategies such as dynamic goal biasing, target switching, and region-based adaptive sampling probability. The improved Bi-APF-RRT* algorithm effectively controls sampling direction and spatial distribution during the path search process, avoiding local optima and significantly improving the success rate and quality of path planning. To validate the performance of the algorithm, this paper conducts a comparative analysis of Bi-APF-RRT* against traditional RRT* in multiple simulation experiments. Quantitative results demonstrate that Bi-APF-RRT* achieves a 59.6% reduction in average computational time (from 5.97 s to 2.41 s), a 20.6% shorter path length (from 691.56 to 549.21), and a lower average path angle (reduced from 33.28° to 29.53°), while maintaining a 100% success rate compared to 95% for RRT*. Additionally, Bi-APF-RRT* reduces the average number of nodes in the search tree by 45.8% (from 381.17 to 206.5), showcasing stronger obstacle avoidance capabilities, faster convergence, and smoother path generation in complex 3D environments. The results highlight the algorithm’s robust adaptability and reliability in UAV path planning.

show abstract

A 3D Path Planning Algorithm for UAVs Based on an Improved Artificial Potential Field and Bidirectional RRT*

Huang,

Li,

Dai

et al. 2024

Drones

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Research on APF-Bi-RRT Algorithm of Adaptive Step Strategy for Robot Path Planning

Cited by 1 publication

References 27 publications

A 3D Path Planning Algorithm for UAVs Based on an Improved Artificial Potential Field and Bidirectional RRT*

A 3D Path Planning Algorithm for UAVs Based on an Improved Artificial Potential Field and Bidirectional RRT*

Contact Info

Product

Resources

About