使用蒙特卡洛树搜索的人机协作

Feng Yao, Huailin Zhao, Huaping Liu
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引用次数: 0

摘要

人机协作作为一项具有挑战性的课题,受到了学术界的广泛关注。现有的许多搜索模型都是针对单智能体或多智能体的,但其任务目标的搜索效率存在一定的缺陷。因此,我们提出了一种室内场景下的人机协同搜索算法,由人和智能体合作完成对相关物体的搜索。我们开发了一个人机协作平台,设计了一套智能体集成场景先验知识、目标识别和路径规划的算法。实验结果表明,我们提出的H-R协同搜索模型在目标搜索任务中具有良好的效率。
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Human-Robot Collaboration using Monte Carlo Tree Search
Human-Robot collaboration as a challenging task has received great attention in the academic research field. Many existing search models are aimed at single agent or multi-agent, but there are some defects in the search efficiency of their task targets. Therefore, we propose a human-computer cooperative search algorithm in the indoor scene, where people and agents cooperate to complete the search of related objects. We have developed a platform for human-robot collaboration, and designed a set of algorithms for agent to integrate scene prior knowledge, target recognition, and path planning. The experimental results that the H-R cooperative search model proposed by us shows good efficiency in target search tasks.
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