Communication components for Human Intention Prediction – A Survey

Fahad Khan, Seemal Asif, P. Webb
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Abstract

In this review we address the communication components for human intention prediction for Human-robot collaboration (HRC). The HRC is the approach in which human and robot(s) work towards achieving the same goal. The interaction can be both levels physical and cognitive. The traditional settings of the HRC system provides fixed robot program based on waypoints or gestures. It is difficult to predefine the instructions of the situation in complex and variable environment. The understanding of human intention on dynamic basis is crucial for the success of such systems. The core character of co-existence of human and the robot is to understand the dynamic scenes of human intentions. To understand the human intention there is need to understand the components of intention communication. This paper provides comprehensive overview about the understanding the intention as communication components and modelling those components by using machine learning technology in HRC. Multiple ways of communicating intention are possible by using speech, action, gesture, haptic, physiological signals, etc. The article details various approaches to understand the human intention communication aspect particularly in the Human Robot Collaboration setting.
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用于人类意图预测的通信组件-调查
在这篇综述中,我们讨论了人机协作(HRC)中人类意图预测的通信组件。HRC是人类和机器人为实现同一目标而工作的方法。这种互动可以是身体和认知层面的。HRC系统的传统设置提供基于路径点或手势的固定机器人程序。在复杂多变的环境中,很难预先定义情境指令。在动态的基础上理解人的意图对这类系统的成功至关重要。人与机器人共存的核心特征是理解人类意图的动态场景。要理解人类的意图,就需要理解意图交流的组成部分。本文全面概述了在HRC中使用机器学习技术将意图理解为通信组件并对这些组件进行建模。通过语言、动作、手势、触觉、生理信号等多种方式表达意图是可能的。本文详细介绍了理解人类意图通信方面的各种方法,特别是在人机协作设置中。
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