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Cross-Country Path Finding using Hybrid approach of BBO and ACO

Author(s): Harish Kundra | Puja | Dr. V.K.Panchal

Journal: International Journal of Computer Applications
ISSN 0975-8887

Volume: 7;
Issue: 6;
Start page: 20;
Date: 2010;
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Keywords: satellite image | Path planning | terrain mapping | obstacle detection and avoidance | and Swarm Intelligence.

Biogeography based optimization (BBO) and ant colonyoptimization (ACO) to develop global optimization path. Innatural scenario, there are no prior paths and we don't haveany prior information about any geographical area. The keyfactor to achieve a task in such area is Path planning;therefore this research direction is very useful in recentyears. This hybrid approach describes autonomousnavigation for outdoor vehicles which includes terrainmapping, obstacle detection and avoidance, and goalseeking in cross-country using Swarm Intelligence. Theseapproaches combine the strengths of both BiogeographyBased Optimization (BBO) for natural and obstacledetection from the satellite image and Ant ColonyOptimization (ACO) algorithm for obstacle avoidance andshortest path to the goal. In this paper this hybrid approachis to explore the improved swarm computing algorithms forthe satellite image obstacle extraction and path planningwhich is safer, shorter, smoother and quickly optimized.

Tango Jona
Tangokurs Rapperswil-Jona

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