| 研究実績の概要 |
In FY2023, we developed object search strategies for service robots in a simulated indoor living lab environment. We designed two distinct methods: one based on heuristic object search and the other on probabilistic inferencing. These techniques are crucial for tasks like object retrieval and detection in home like settings, where users might ask robots to locate specific items. Our approach integrated open-source datasets to train object classifications, incorporating them into our semantic life-long mapping framework.
Additionally, we created room and region classification algorithms to establish semantic connections between objects, places, and regions. This resulted in a three-layer semantic map, enhancing robot navigation and human robot interaction.
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