HATP/EHDA:机器人任务规划器预测和引出人类的决策和行动

Guilhem Buisan, Anthony Favier, Amandine Mayima, R. Alami
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引用次数: 5

摘要

自主机器人可以处理的任务的多样性和复杂性不断增加,但我们很少看到机器人与人类合作。事实上,人类要么被要求准时提供帮助,要么被赋予整个任务的领导权。我们提出了一种人类感知任务规划方法,允许机器人在规划任务的同时考虑和模仿人类的决策、行动和反应过程。我们的方法,名为人类感知任务规划器与模拟人类决策和行动(HATP/EHDA),是基于对多个分层任务网络的探索,尽管不同的代理是否被认为是可控的(机器人)或不可控的(人类)。我们提出了我们的方法的基本原理以及形式化,并通过一个说明性示例展示了它的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HATP/EHDA: A Robot Task Planner Anticipating and Eliciting Human Decisions and Actions
The variety and complexity of tasks autonomous robots can tackle is constantly increasing, yet we seldom see robots collaborating with humans. Indeed, humans are either requested for punctual help or are given the lead on the whole task. We propose a human-aware task planning approach allowing the robot to plan for a task while also considering and emulating the human decision, action, and reaction processes. Our approach, named Human-Aware Task Planner with Emulation of Human Decisions and Actions (HATP/EHDA), is based on the exploration of multiple hierarchical tasks networks albeit differently whether the agent is considered to be controllable (the robot) or uncontrollable (the human). We present the rationale of our approach along with a formalization and show its potential on an illustrative example.
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