OmniRace：用于竞速无人机直观引导的6D手部姿态估计
OmniRace: 6D Hand Pose Estimation for Intuitive Guidance of Racing Drone
AI总结：
本文提出OmniRace，首次利用6D手部姿态估计和手势识别实现竞速无人机的低层级直观控制，实验表明其使赛道完成时间缩短25.1%，路径长度从102.9米降至83.7米，神经网络平均准确率达99.75%。
摘要：
本文提出了OmniRace方法，通过6自由度（DoF）手部姿态估计和手势识别来控制竞速无人机。据我们所知，这是首个允许通过手势对高速无人机进行低层级控制的技术。OmniRace采用基于计算机视觉和深度神经网络的手势接口来估计6-DoF手部姿态。先进的机器学习算法能够稳健地解读人类手势，使用户能够直观地控制无人机运动。对竞速无人机的实时控制证明了该系统的有效性，验证了其革新无人机竞速及其他应用的潜力。在Gazebo仿真环境中进行的实验结果表明，OmniRace使用户完成无人机竞速赛道的时间显著缩短（缩短25.1%），并将测试无人机路径长度从102.9米减少到83.7米。用户在手势界面的吸引力（UEQ得分1.57）、享乐质量（UEQ得分1.56）和较低的感知时间需求（NASA-TLX得分32.0）方面表现出偏好，同时指出基线遥控器具有高效率（UEQ得分0.75）和低体力需求（NASA-TLX得分19.0）。该深度神经网络在归一化数据集和原始数据集上均达到99.75%的平均准确率。OmniRace有望改变人类在动态复杂环境中与竞速无人机交互和导航的方式。源代码可在https://github.com/SerValera/OmniRace.git获取。
英文摘要：
This paper presents the OmniRace approach to controlling a racing drone with 6-degree of freedom (DoF) hand pose estimation and gesture recognition. To our knowledge, it is the first-ever technology that allows for low-level control of high-speed drones using gestures. OmniRace employs a gesture interface based on computer vision and a deep neural network to estimate a 6-DoF hand pose. The advanced machine learning algorithm robustly interprets human gestures, allowing users to control drone motion intuitively. Real-time control of a racing drone demonstrates the effectiveness of the system, validating its potential to revolutionize drone racing and other applications. Experimental results conducted in the Gazebo simulation environment revealed that OmniRace allows the users to complite the UAV race track significantly (by 25.1%) faster and to decrease the length of the test drone path (from 102.9 to 83.7 m). Users preferred the gesture interface for attractiveness (1.57 UEQ score), hedonic quality (1.56 UEQ score), and lower perceived temporal demand (32.0 score in NASA-TLX), while noting the high efficiency (0.75 UEQ score) and low physical demand (19.0 score in NASA-TLX) of the baseline remote controller. The deep neural network attains an average accuracy of 99.75% when applied to both normalized datasets and raw datasets. OmniRace can potentially change the way humans interact with and navigate racing drones in dynamic and complex environments. The source code is available at https://github.com/SerValera/OmniRace.git.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
