Centre for Automation and Robotics, Consejo Superior de Investigaciones Cientificas-UPM, Ctra. Campo Real km 0.2, La Poveda, Arganda del Rey, Madrid, 28500, Spain.
Sensors (Basel). 2011;11(10):9393-410. doi: 10.3390/s111009393. Epub 2011 Sep 29.
The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person's body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person's foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps.
如今,人员在室内环境中的定位仍是一个开放性问题。有一些基于部署传感器网络(位置定位系统或 LPS)的部分解决方案。其他解决方案只需要在人员身体上安装惯性传感器(行人航位推算或 PDR)。PDR 解决方案集成了来自惯性测量单元(IMU)的信号,该单元通常包含 3 个加速度计和 3 个陀螺仪。PDR 的主要问题是由于传感器噪声引起的漂移而导致的定位误差的累积。本文提出了一种 PDR 解决方案,该方案包含一种基于检测建筑物中通常存在的入口斜坡的漂移校正方法。斜坡校正方法在基于惯性导航算法(INS)和附在人脚的 IMU 的 PDR 框架上实现。与使用外部传感器校正漂移误差的其他方法不同,我们仅在脚上使用一个 IMU。为了检测斜坡,从 IMU 中估计用户正在行走的地形的斜率以及向前移动时感觉到的高度变化。检测到斜坡后,会检查其是否与数据库中现有的斜坡之一相关联。对于每个相关联的斜坡,都会向卡尔曼滤波器提供位置校正,以改进 INS-PDR 解决方案。在建筑物中,对于长 1000 米的路线,定位误差低于 2 米,实现了无漂移的定位。