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Adaptive Question Generation for Ambiguous Robot Instructions Based on Information Gain and Human Cognitive Characteristics
In this study, we propose an adaptive question generation mechanism that addresses uncertainty arising from ambiguous instructions. Natural-language instructions for service robots often contain ambiguities. In scenes with multiple similar objects, the robot must identify the target object by asking
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