Multi-Strategy Fusion Improves Time Optimal Trajectory Planning of Particle Swarm Optimization Algorithm

A multi-strategy improved particle swarm optimization algorithm is proposed to optimize the time-optimal trajectory for robot joint space, achieving an accuracy improvement of 12.8% to 45.3% and a stability enhancement of 38.7% to 66.1%.

Authors

Publication Details

Journal
ES General
Published
2025-01-01
DOI
https://doi.org/10.30919/esg1515
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-Strategy Fusion Improves Time Optimal Trajectory Planning of Particle Swarm Optimization Algorithm

Haoshen Ye, Weiwei Zhao
ES General
Robotic Path Planning Algorithms
article

Multi-Strategy Fusion Improves Time Optimal Trajectory Planning of Particle Swarm Optimization Algorithm

Haoshen Ye, Weiwei Zhao
article en

Abstract

A multi-strategy improved particle swarm optimization algorithm is proposed to optimize the time-optimal trajectory for robot joint space, achieving an accuracy improvement of 12.8% to 45.3% and a stability enhancement of 38.7% to 66.1%.

ES General
Openalex Percentile: Top 91%
Robotic Path Planning Algorithms
DOIOpen Access PDFOpenAlex
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.

Multi-Strategy Fusion Improves Time Optimal Trajectory Planning of Particle Swarm Optimization Algorithm — Haoshen Ye, Weiwei Zhao · ES General (2025) | TGRS Research Map | TGRS