Abstract
In real-world task planning, such as automatic vehicles dispatch, often face the arrival of new tasks and uncertain factors in the process of task execution. As a typical implementation of Hierarchical Task Network (HTN) planning, JSHOP2 planner is suitable for complex task planning. Given the fact that JSHOP2 planner fails to get planning results in the global level when facing uncertain factors, an improved JSHOP2 planner is proposed to solve this problem. The improved JSHOP2 planner with manual intervention supplements the planning result and eliminates the impact of uncertain factors with the help of human experience. In addition, we conducted comparative experiments based on improved planner. The simulation results show the effectiveness and the ability to emergency response of improved planner.
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Acknowledgment
This research is supported in part by the National Natural Science Foundation of China under Grant No. 61571066, No. 61602054, (NSFC, 61571066, 61602054).
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Tao, L., Sun, Q., Li, J., Zhou, A., Wang, S. (2020). Task Planning with Manual Intervention Using Improved JSHOP2 Planner. In: Hsu, CH., Kallel, S., Lan, KC., Zheng, Z. (eds) Internet of Vehicles. Technologies and Services Toward Smart Cities. IOV 2019. Lecture Notes in Computer Science(), vol 11894. Springer, Cham. https://doi.org/10.1007/978-3-030-38651-1_5
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DOI: https://doi.org/10.1007/978-3-030-38651-1_5
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