環境変化による誘拐状態抑制のための物体の属性を考慮した自己位置推定

抄録

To prevent occurring robot kidnapped problem, it is important to evaluate likelihood of each particle considering an environmental change. Moving objects are one of the main causes of environmental change and each objects has each own movability. For example, chair has high movability because it is designed to move and interacts often with humans. On the other hand, walls or shelves have low movability because they are designed not to move and interact less often with humans. So, in this study, we define classes of objects and movability of them. We propose a localization approach that focuses on the association between sensor information obtained from objects whose movability is low and prior map by considering classes and movability in order to prevent occurring robot kidnapped problem.