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Design of Natural Human-Computer Interaction for Unmanned Delivery Vehicle Based on Kinect

机译:基于Kinect的无人交付车辆自然人计算机互动设计

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摘要

There are more and more application scenarios for unmanned delivery vehicles, and traditional human-computer interaction methods can no longer meet different task scenarios and user needs. The primary purpose of this paper is to apply natural human-computer interaction technology to the field of unmanned delivery, changing the traditional mode that users can only operate unmanned delivery vehicles through the touch screen to complete tasks. The task scenarios of unmanned delivery vehicles are classified through the concept of context. Participatory design and heuristic research are used to allow users to define interactive gestures. Two groups of gesture interaction set that meet different task scenarios and can be accepted and understood by general users are designed. Based on Kinect's deep imaging and bone tracking technology, large number of preset gesture samples are collected, and the Adaboost algorithm is used for machine training to realize gesture interaction. Through recognition and detection, it is proved that the gesture recognition achieved by this method has a high recognition rate and responding speed. Finally, based on Unity 3D, the task scene of the real unmanned delivery vehicle is simulated in the virtual scene. Through the usability test of the human-computer interaction system, it is concluded that this interaction mode guarantees the task efficiency to a certain extent and improves the user experience.
机译:无人驾驶车辆还有越来越多的应用场景,传统的人机交互方法不再符合不同的任务场景和用户需求。本文的主要目的是将天然人机交互技术应用于无人交付领域,改变了用户只能通过触摸屏操作无人驾驶车辆来完成任务。无人交付车辆的任务方案通过上下文的概念分类。参与式设计和启发式研究用于允许用户定义交互式手势。设计了两组符合不同任务场景的手势交互集,并可通过普通用户接受和理解。基于Kinect的深度成像和骨跟踪技术,收集大量预设手势样本,Adaboost算法用于机器训练以实现手势交互。通过识别和检测,证明该方法实现的手势识别具有高识别率和响应速度。最后,基于Unity 3D,在虚拟场景中模拟真实无人送送车的任务场景。通过人机交互系统的可用性测试,得出结论,这种交互模式确保了一定程度的任务效率并提高了用户体验。

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