基于stm32开发的usb hid 复合设备-键盘、鼠标、游戏pad，利用重力感应控制PC游戏。 演示视频： QQ飞车测试：

dwg文件，颗粒堆积模型，可导入COMSOL、ANSYS、Workben、Abaqus、LS-DYNA 、Fluent等有限元软件进行模拟。堆积材料、颗粒材料等的自然状态。

国外大牛写的，基于重力传感器和陀螺仪来检测方向和动作，里面有不少关于算法的细节描述，值得参考！

六维力传感器的工业机器人末端重力补偿算法

重力随高度变化

重力感应主要是依靠手机的加速度传感器(accelerometer)来实现 在Android的开发中一共有八种传感器但是不一定每一款真机都支持这些传感器。因为很多功能用户根本不care的所以可能开发商会把某些功能屏蔽掉。还是得根据真机的实际情况来做开发，今天我们主要来讨论加速度传感器的具体实现方式。

加速度传感器，重力传感器，线性加速度传感器

简要介绍了EGM2008地球重力场模型，利用分布于我国东部平原地区，中部丘陵地带和西部高原山区的4个测量项目的数据，对EGM2008地球重力场模型的精度进行了分析，并对该模型在不同地形条件下的应用方法进行了探索。

全球重力场模型下载 EGM2008.gfc重力场模型数据下载

XGM2019e is a combined global gravity field model represented through spheroidal harmonics up to d/o 5399, corresponding to a spatial resolution of 2’ (~4 km). As data sources it includes the satellite model GOCO06s in the longer wavelength area combined with terrestrial measurements for the shorter wavelengths. The terrestrial data itself consists over land and ocean of gravity anomalies provided by courtesy of NGA (identical to XGM2016, having a resolution of 15’) augmented with topographically derived gravity over land (EARTH2014). Over the oceans, gravity anomalies derived from satellite altimetry are used (DTU13, in consistency with the NGA dataset). The combination of the satellite data with the terrestrial observations is performed by using full normal equations up to d/o 719 (15’). Beyond d/o 719, a block-diagonal least-squares solution is calculated for the high-resolution terrestrial data (from topography and altimetry). All calculations are performed in the spheroidal harmonic domain. In the spectral band up to d/o 719 the new model shows over land a slightly improved behavior over preceding models such as XGM2016, EIGEN6c4 or EGM2008 when comparing it to independent GPS leveling data. Over land and in the spectral range above d/o 719 the accuracy of XGM2019e slightly suffers from the sole use oftopographic forward modelling; Hence, errors are increased in well-surveyed areas compared to models containing real gravity data, e.g. EIGEN6c4 or EGM2008. However, the performance of XGM2019e can be considered as globally more homogeneous and independent from existing high resolution global models. Over the oceans the model exhibits an improved performance throughout the complete spectrum (equal or better than preceding models).