Service planning oriented efficient object search: A knowledge-based framework for home service robot
2022
Abstract In the unstructured family environment, robots are expected to provide various services to improve the quality of human life, based on the performance of specific action sequences generated by service planning. This paper focuses on one of the greatest challenges in service planning that is aimed at accomplishing the service tasks by generating appropriate object sequences to guide the robot on searching the corresponding target objects efficiently and reasonably. A well-structured knowledge-based framework of object search is proposed in our approach as well as taking into account the multi-domain knowledge of applying object, scene, and service in design. In order to improve the searching efficiency and reasonability, an ontology-based hierarchical and interrelated knowledge structure is formed to support the implementation of complicated service planning with either single or multiple tasks. The proposed framework is tested by comprehensive experiments, and the performance is evaluated with other mainstream methods in both simulation and real-world environments. The experimental results demonstrate the feasibility and effectiveness of applying this knowledge-based framework to efficient object searching aspect in service planning.
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