Applying Center Loss to Multidimensional Feature Space in Deep Neural Networks for Open-set Recognition

Kanaoka, Daiju; Tanaka, Yuichiro; Tamukoh, Hakaru

doi:10.5220/0010816600003124

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2024

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“…Recently, the demand for home service robots has been increasing due to a low birth rate and an aging population, and research on such robots has been active [1], [2], [3], [4], [5], [6]. Highly accurate task planning is necessary to realize a general-purpose service robot that performs appropriate actions in response to human requests.…”

Section: Introductionmentioning

confidence: 99%

Development of A SayCan-based Task Planning System Capable of Handling Abstract Nouns

Yamao,

Kanaoka,

Isomoto

et al. 2024

Proceedings of International Conference on Artificial Life and Robotics

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The task planning system is required to accomplish various requests from a human in real-world environments. SayCan, one of the task planning systems, has high accuracy. However, its accuracy decreases for requests that include abstract nouns of the ambiguous word/phrase. We propose a novel task planning system based on SayCan that introduces a function for checking concrete names of abstract nouns and a rule-based skill extraction, enhancing accuracy. The proposed system facilitates the interpretation of requests and enables appropriate task planning. The effectiveness of the proposed system was demonstrated at RoboCup@Home, where it achieved high performance.

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Section: Introductionmentioning

confidence: 99%