Study on Path Planning based on Artificial Potential Field using Triangular Target Strategy

Path planning algorithms are essential to ensure that mobile robots reach their target smoothly. Artificial Potential field (APF) is a traditional path planning algorithm, which is widely used in the local path planning algorithm of mobile robots because of its advantages of small computation, easy to understand and easy to implement. The problems of unreachable target and local minimum exist in traditional APF. To solve these two problems, APF is improved in this paper. Aiming at the unreachable target, this paper introduces adjusting factor into the repulsion potential field function to make the target become the lowest potential energy and ensure that the robot can reach the target. To solve the local minimum problem, this paper presents a triangular target strategy, which can select a suitable virtual target to introduce additional external forces, so as to break the robot's equilibrium state. Simulation results show that the improved APF successfully solves the above two problems.

Authors

Institutions

Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/icocta64736.2024.00026
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study on Path Planning based on Artificial Potential Field using Triangular Target Strategy

Yunlong Zhuang, Wenxing Zhu
Robotic Path Planning Algorithms
article

Study on Path Planning based on Artificial Potential Field using Triangular Target Strategy

Yunlong Zhuang, Wenxing Zhu
article en

Abstract

Path planning algorithms are essential to ensure that mobile robots reach their target smoothly. Artificial Potential field (APF) is a traditional path planning algorithm, which is widely used in the local path planning algorithm of mobile robots because of its advantages of small computation, easy to understand and easy to implement. The problems of unreachable target and local minimum exist in traditional APF. To solve these two problems, APF is improved in this paper. Aiming at the unreachable target, this paper introduces adjusting factor into the repulsion potential field function to make the target become the lowest potential energy and ensure that the robot can reach the target. To solve the local minimum problem, this paper presents a triangular target strategy, which can select a suitable virtual target to introduce additional external forces, so as to break the robot's equilibrium state. Simulation results show that the improved APF successfully solves the above two problems.

Shandong University (CN)
Ministry of Education, Natural Science Foundation of Shandong Province, Research and Development
Openalex Percentile: Top 71%
Robotic Path Planning Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Study on Path Planning based on Artificial Potential Field using Triangular Target Strategy — Yunlong Zhuang, Wenxing Zhu · (2024) | TGRS Research Map | TGRS