RBT-HCI: A Reliable Behavior Tree Planning Method with Human-Computer Interaction

Yunlong Wu, Jinghua Li, Haoxiang Jin, Jiexin Zhang, Yanzhen Wang
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引用次数: 1

Abstract

In this paper, we propose RBT-HCI, a reliable behavior tree (BT) planning method with human-computer interaction, aiming at generating an interpretable and human-acceptable BT. Compared with other BT generation methods, RBT-HCI can reliably plan a BT based on the knowledge base. When an available BT cannot be planned automatically, instead of terminating or relaxing the rules, RBT-HCI provides a new idea, which is to make decisions through human-computer interaction, thereby enhancing the reliability and robustness of the method. The effectiveness of RBT-HCI is verified by an example of robot grasping objects, showing that a reliable and robust planning result can be obtained through knowledge-based automatic planning and human-computer interaction.
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RBT-HCI:一种可靠的人机交互行为树规划方法
本文提出了基于人机交互的可靠行为树规划方法RBT-HCI,旨在生成可解释且人类可接受的行为树,与其他行为树生成方法相比,RBT-HCI可以基于知识库可靠地规划行为树。当可用BT无法自动规划时,RBT-HCI提供了一种新的思路,即通过人机交互进行决策,从而增强了方法的可靠性和鲁棒性,而不是终止或放松规则。通过机器人抓取物体的实例验证了RBT-HCI的有效性,表明通过基于知识的自动规划和人机交互可以获得可靠的鲁棒规划结果。
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