For this reason, we defined eight most common motion states during pedestrian navigation in this paper. In order to classify the motion states, twenty-seven features are investigated in this section.3.1. Motion DefinitionThe selleck inhibitor motion states, as defined in Table 1, are grouped into four series as follows:S-series motion states (Figure 1) refer to the stationary behavior during a navigation process. ST is a state where a user keeps a phone in hand without any movement. In contrast, SS is a category of the movement where user’s location does not change, but the phone is moving in a swinging.Figure 1.S-series (left and middle: ST, right: SS).W-series is relevant to walking. After observing the walking behaviour of the user when navigating, three types of walking motion states have been defined.
As shown in the left image of Figure 2, WH represents the motion state where the user is using the navigation application on the handset while walking. The user often keeps his or her eyes on the screen of a smartphone in this state. WS stands for the normal walking behaviour, when the user is not using the navigation application but is holding the smartphone in his or her hand. As the center image of Figure 2 indicates, a small arm swinging motion exists when the user is walking in normal speed, while the right image of Figure 2 shows the WF state, which represents a fast walking behaviour with significantly arm swinging.Figure 2.W-series (left: WH, middle: WS, and right: WF).T-series is related to turning motions. UT represents so-called U-turning, which is a spot turn without any horizontal displacement.
As shown in Figure 3, a UT motion results in a heading change of 180�� after turning.Figure 3.T-series (UT).V-series concerns motions in the vertical dimension. In Figure 4, US and DS are going up/down the stairs, respectively.Figure 4.V-series (left: US and right: DS).Table 1.Motion state definition.3.2. Feature DefinitionWhen using tri-axis accelerometer sensors, the sensor orientation determines the local coordinate system of each (x, y, z) reading. Most previous research work on motion recognition has used body-worn accelerometer sensors, i.e., sensors attached to the body in a constrained Entinostat orientation. When smartphones are used as portable sensors, the orientatio
With the development of mechatronics, automatic systems consisting of sensors for perception and actuators for action are more and more widely used in applications [1�C4].
Besides the proper choices of sensors and actuators and an elaborate fabrication of mechanical structures, the control law design also plays a crucial role in the implementation of automatic systems especially for those with complicated dynamics. For most mechanical sensor-actuator systems, it is possible to model them in Euler-lagrange equations http://www.selleckchem.com/products/Imatinib(STI571).html [4,5].