Human Clustering for A Partner Robot Based on Particle Swarm Optimization
説明
This paper proposes swarm intelligence for a perceptual system of a partner robot. The robot requires the capability of visual perception to interact with a human. Basically, a robot should perform moving object extraction and clustering for visual perception used in the interaction with a human. In this paper, we propose a total system for human classification for a partner robot by using particle swarm optimization, k-means, self organizing maps and back propagation. The experimental results show that the partner robot can perform the human clustering and classification.
収録刊行物
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- ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication
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ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication 686-691, 2006-09-01
IEEE
