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利用 Leap Motion 传感器进行手部追踪的精度和稳定性分析。

Analysis of Precision and Stability of Hand Tracking with Leap Motion Sensor.

机构信息

Department of Robotics, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic.

Department of Robotics, Faculty of Mechanical Engineering, Technical University of Kosice, 04200 Kosice, Slovakia.

出版信息

Sensors (Basel). 2020 Jul 22;20(15):4088. doi: 10.3390/s20154088.

DOI:10.3390/s20154088
PMID:32707927
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7436110/
Abstract

In this analysis, we present results from measurements performed to determine the stability of a hand tracking system and the accuracy of the detected palm and finger's position. Measurements were performed for the evaluation of the sensor for an application in an industrial robot-assisted assembly scenario. Human-robot interaction is a relevant topic in collaborative robotics. Intuitive and straightforward control tools for robot navigation and program flow control are essential for effective utilisation in production scenarios without unnecessary slowdowns caused by the operator. For the hand tracking and gesture-based control, it is necessary to know the sensor's accuracy. For gesture recognition with a moving target, the sensor must provide stable tracking results. This paper evaluates the sensor's real-world performance by measuring the localisation deviations of the hand being tracked as it moves in the workspace.

摘要

在本分析中，我们展示了为确定手部跟踪系统的稳定性和检测到手部和手指位置的准确性而进行的测量结果。这些测量是为了评估传感器在工业机器人辅助装配场景中的应用而进行的。人机交互是协作机器人中的一个相关主题。对于在生产场景中有效地利用机器人，直观和直接的机器人导航和程序流控制工具对于避免因操作员造成的不必要的减速是至关重要的。对于手部跟踪和基于手势的控制，需要知道传感器的准确性。对于移动目标的手势识别，传感器必须提供稳定的跟踪结果。本文通过测量在工作空间中移动的手部的定位偏差来评估传感器的实际性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/436b7eb419a5/sensors-20-04088-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/f7a3f0a64552/sensors-20-04088-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/3305b0d449c0/sensors-20-04088-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/6b9a19d49cfb/sensors-20-04088-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/b581e12206f9/sensors-20-04088-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/99abb4c6828d/sensors-20-04088-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/30b9c6e4bc87/sensors-20-04088-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/575b9e1e1f7b/sensors-20-04088-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/11e661169109/sensors-20-04088-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/436b7eb419a5/sensors-20-04088-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/f7a3f0a64552/sensors-20-04088-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/3305b0d449c0/sensors-20-04088-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/6b9a19d49cfb/sensors-20-04088-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/b581e12206f9/sensors-20-04088-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/99abb4c6828d/sensors-20-04088-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/30b9c6e4bc87/sensors-20-04088-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/575b9e1e1f7b/sensors-20-04088-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/11e661169109/sensors-20-04088-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe8b/7436110/436b7eb419a5/sensors-20-04088-g009.jpg

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Validation of the Leap Motion Controller using markered motion capture technology.使用带标记的运动捕捉技术对Leap Motion控制器进行验证。
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Human-Robot Interaction: Status and Challenges.人机交互：现状与挑战。
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Tracking of Gymnast's Limb Movement Trajectory Based on MEMS Inertial Sensor.基于MEMS惯性传感器的体操运动员肢体运动轨迹跟踪
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