The satellite technology proves its impact in the modern era with itswide benefits and applications. However, the cost of the development in this fieldpresents gaps in many countries, almost the developed countries. T...The satellite technology proves its impact in the modern era with itswide benefits and applications. However, the cost of the development in this fieldpresents gaps in many countries, almost the developed countries. Therefore, thispaper provides a rich platform around low-cost sensors in order to improve maturity in space technology, mostly the system of attitude determination and control.The development of this knowledge turns out to be very interesting in order toachieve a space mission which leads to the progression of the spatial technologyreadiness level (TRL) defined by the international measurement scale which isable to estimate the technological maturity. Thus, the idea is carried out for thedevelopment of low-cost sensors’ system for attitude determination around anArduino board. A sensor fusion method was applied on three types of sensors:accelerometer, magnetometer, and gyroscope in order to detect the reliable orientation. It is aimed to apply quaternion based Kalman filter on different platformthan previous systems. It is succeeded therefore to improve measurementaccuracy around low-cost sensor to achieve the main goal of this paper.展开更多
针对视觉SLAM(simultaneous localization and mapping)算法在动态环境下容易出现重定位失败的问题,提出了一种基于自身运动约束的动态SLAM算法。采用YOLOv5s初步区分前景与背景特征点,仅利用背景特征点进行位姿初始化;利用IMU位姿信息...针对视觉SLAM(simultaneous localization and mapping)算法在动态环境下容易出现重定位失败的问题,提出了一种基于自身运动约束的动态SLAM算法。采用YOLOv5s初步区分前景与背景特征点,仅利用背景特征点进行位姿初始化;利用IMU位姿信息不受动态环境影响的特性,计算每个特征点的自身运动约束值;根据背景特征点的特征约束结果设计了动态概率模型,自适应确定当前帧特征点约束的动态阈值,去除动态特征点并更新相机位姿。使用仿真数据集和真实环境数据集进行了实验验证。实验结果表明,在仿真数据集中,该方法能去除沿极线运动的特征点,相较于Dyna-SLAM,在均方根误差和标准差两项指标的提升率为87.81%和83.17%,相较于AirDos提升率分别为51.62%和41.91%。真实动态环境中重定位能力强于Dyna-SLAM,较AirDos无明显精度提升但运行速度提升29.48%。展开更多
Mini IMU姿态传感器中带有三轴陀螺仪和三轴加速度计,利用其模块放置在机器人可以实现机器人的姿态显示。履带式机器人在灾后进行巡检搜救,对陌生的地形情况,姿态信息显得极为重要。对此,将Mini IMU模块连接在机器人主控板上面,在飞思卡...Mini IMU姿态传感器中带有三轴陀螺仪和三轴加速度计,利用其模块放置在机器人可以实现机器人的姿态显示。履带式机器人在灾后进行巡检搜救,对陌生的地形情况,姿态信息显得极为重要。对此,将Mini IMU模块连接在机器人主控板上面,在飞思卡尔DP512单片机μC/OS-II操作系统中,将数据整合转发给上位机,上位机软件接受到数据信息后,进行数据处理,再用OpenGL虚拟现实技术将机器人姿态复原在上位机中。完成整个设计后,实际让机器人进行旋转、攀爬,和在上位机中得到的数据进行对比测量实验,用误差分析的方法对实验结果分析及评估,具有较强的实时性、准确性、可靠性。展开更多
基金funded this work through Taif University Research Supporting,Project Number(TURSP-2020/277),Taif University,Taif,Saudi Arabia.
文摘The satellite technology proves its impact in the modern era with itswide benefits and applications. However, the cost of the development in this fieldpresents gaps in many countries, almost the developed countries. Therefore, thispaper provides a rich platform around low-cost sensors in order to improve maturity in space technology, mostly the system of attitude determination and control.The development of this knowledge turns out to be very interesting in order toachieve a space mission which leads to the progression of the spatial technologyreadiness level (TRL) defined by the international measurement scale which isable to estimate the technological maturity. Thus, the idea is carried out for thedevelopment of low-cost sensors’ system for attitude determination around anArduino board. A sensor fusion method was applied on three types of sensors:accelerometer, magnetometer, and gyroscope in order to detect the reliable orientation. It is aimed to apply quaternion based Kalman filter on different platformthan previous systems. It is succeeded therefore to improve measurementaccuracy around low-cost sensor to achieve the main goal of this paper.
文摘针对视觉SLAM(simultaneous localization and mapping)算法在动态环境下容易出现重定位失败的问题,提出了一种基于自身运动约束的动态SLAM算法。采用YOLOv5s初步区分前景与背景特征点,仅利用背景特征点进行位姿初始化;利用IMU位姿信息不受动态环境影响的特性,计算每个特征点的自身运动约束值;根据背景特征点的特征约束结果设计了动态概率模型,自适应确定当前帧特征点约束的动态阈值,去除动态特征点并更新相机位姿。使用仿真数据集和真实环境数据集进行了实验验证。实验结果表明,在仿真数据集中,该方法能去除沿极线运动的特征点,相较于Dyna-SLAM,在均方根误差和标准差两项指标的提升率为87.81%和83.17%,相较于AirDos提升率分别为51.62%和41.91%。真实动态环境中重定位能力强于Dyna-SLAM,较AirDos无明显精度提升但运行速度提升29.48%。
