Using Constraints for Shoe Mounted Indoor Pedestrian Navigation

Abstract

Shoe mounted Inertial Measurement Units (IMU) are often used for indoor pedestrian navigation systems. The presence of a zero velocity condition during the stance phase enables Zero Velocity Updates (ZUPT) to be applied regularly every time the user takes a step. Most of the velocity and attitude errors can be estimated using ZUPTs. However, good heading estimation for such a system remains a challenge. This is due to the poor observability of heading error for a low cost Micro-Electro-Mechanical (MEMS) IMU, even with the use of ZUPTs in a Kalman filter. In this paper, the same approach is adopted where a MEMS IMU is mounted on a shoe, but with additional constraints applied. The three constraints proposed herein are used to generate measurement updates for a Kalman filter, known as ‘Heading Update’, ‘Zero Integrated Heading Rate Update’ and ‘Height Update’.The first constraint involves restricting heading drift in a typical building where the user is walking. Due to the fact that typical buildings are rectangular in shape, an assumption is made that most walking in this environment is constrained to only follow one of the four main headings of the building. A second constraint is further used to restrict heading drift during a non-walking situation. This is carried out because the first constraint cannot be applied when the user is stationary. Finally, the third constraint is applied to limit the error growth in height. An assumption is made that the height changes in indoor buildings are only caused when the user walks up and down a staircase. Several trials were shown to demonstrate the effectiveness of integrating these constraints for indoor pedestrian navigation. The results show that an average return position error of 4·62 meters is obtained for an average distance of 1557 meters using only a low cost MEMS IMU.

An open source inertial sensor network with Bluetooth Smart

“…Some indoor navigation systems incorporate the PNS with computer vision for better accuracy. Recently, new developments in PNS have made it possible to be a standalone navigation system inside buildings [6] [3] [7].…”

“…Indoor navigation [6] Jungles, forests, and underground caves Support GPS for consistent navigation [5] Gyms, laboratories, physical activity researches Plot and analyze user actions for fitness, performance, and sports [4] Hospitals, home Measure patient exercises for rehabilitation [1] Anime, Computer Graphics, Movies,…”

“…the heading is always along the hallway; the heading remains constant at stop; the elevation doesn't change anywhere else except on staircases [6]. These assumptions enabled constraints on the heading, the heading drifts at rest, and the error growths on height.…”

A Pedestrian Navigation System Based on Low Cost IMU

“…Height Constraint. Similar to the concept proposed by Abdulrahim et al (2012), we assume that the changes in height are only caused by climbing stairs since the floor is level in most indoor environments. If a change in height over one step is above a threshold, we regard it as reaching a new level or a stair; otherwise the height will be maintained at the previous level and uses this as a measurement of the Kalman filter.…”

“…C U P T. As mentioned by Abdulrahim et al (2012), ZUPT will fail in two situations such as on an elevator or escalator. This is due to the fact that the stance phases detected on a moving platform are not zero velocity.…”