Hierarchical detecting points path planning algorithm for climbing robot in spatial trusses

To solve climbing robot path planning in spatial trusses with detecting points, a hierarchical algorithm is proposed according to the divide-and-conquer strategy. Path planning problem with large-scale detecting points is decomposed into a number of path planning sub-problems with small-scale detect...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:2017 International Conference on Robotics and Automation Sciences (ICRAS) S. 25 - 29
Hauptverfasser: Erchong Liao, Changan Liu, Limei Jiang
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.08.2017
Schlagworte:
Algorithm design and analysis
ant colony optimization algorithm
Classification algorithms
climbing robot
Climbing robots
Clustering algorithms
density peaks clustering algorithm
Path planning
Runtime
traveling salesman problem
ISBN:1538639947, 9781538639948
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:To solve climbing robot path planning in spatial trusses with detecting points, a hierarchical algorithm is proposed according to the divide-and-conquer strategy. Path planning problem with large-scale detecting points is decomposed into a number of path planning sub-problems with small-scale detecting points by Density Peaks Clustering algorithm(DPC), and then all sub-problems with small-scale detecting points are resolved by Ant Colony Optimization algorithm(ACO). At last, all the paths obtained from each subproblem are merged, and local path is optimized by 2-Opt and 3-Opt algorithms. The hierarchical algorithm is tested on 5 different instances. Experimental results show that the proposed algorithm has the same accuracy and computational complexity can be decreased n squared compared with ACO algorithm. The efficiency has been significantly improved.
ISBN:1538639947
9781538639948
DOI:10.1109/ICRAS.2017.8071910