Gyroscope

In this research, a gyroscope is used for detecting the unmanned vehicle’s orientation or so-called heading angle, and to find the gain value of the PID controller. Generally speaking, a gyroscope can be used to perform dead reckoning navigation [Bor96]. Dead reckoning is defined as estimating positions by calculating the distance, direction, and amount of time that a vehicle has traveled. Dead reckoning provides navigators with a way to quickly and efficiently calculate their vehicle's position with reasonable accuracy as they travel.

Boaters, pilots, and other navigators use dead reckoning position when they are offshore or near shore when fog or darkness obscures visual position clues. Sailors and pilots of small aircraft also use dead reckoning to estimate the time they will arrive at their destination.

A ship, airplane, or vehicle following a compass course travels on an imaginary line called a Path. If a navigator knows the track, the coordinates of the starting position, and the distance covered, the navigator can estimate the vehicle's position. To calculate the distance-run, or the distance covered, a navigator needs to know only the speed and the amount of time traveled.

Any rotating body exhibits two fundamental properties:

gyroscopic inertia, or rigidity in space, and precession, the tilting of the axis at right angles to any force tending to alter the plane of rotation.

These properties are inherent in all rotating bodies, including the earth itself. The term gyroscope is commonly applied to spherical, wheel-shaped, or disk-shaped bodies that are universally mounted to be free to rotate in any direction. They are used to demonstrate these properties or to indicate movements in space.

The rigidity in space of a gyroscope is a consequence of Newton's first law of motion, which states that a body tends to continue in its state of rest or uniform motion unless subject to outside forces.

Thus, the wheel of a gyroscope, when started spinning, tends to continue to rotate in the same plane about the same axis in space. An example of this tendency is a spinning top, which has freedom about two axes in addition to the spinning axis. Another example is a rifle bullet that, because it spins or revolves in flight, exhibits gyroscopic inertia, tending to maintain a straighter line of flight than it would if not rotating.

In the research area of navigation systems, there are two positioning systems employed together: absolute and relative

positioning methods.

Absolute positioning methods usually rely on navigation beacons, active or passive landmarks, map matching, or satellite-based navigation signals. Each of these absolute positioning approaches can be implemented by a variety of methods and sensors. Yet, these systems are too expensive to be used as personal equipment. If the position of these external references is known, then the position of the unmanned vehicle can be calculated, usually with good accuracy. The problem with most absolute positioning methods is that they require modifications of the environment prior to utilizing the system.

Relative positioning is usually based on an odometer, which is cheap, simple, and easy to mock up, however, it has the unsolvable serious problem of unbounded accumulation of error. By imperceptive degrees, the error grows more and more. However, it does not need any external reference, such as encoders for odometry and gyroscopes or accelerometers for inertial measurements. The advantage of these systems is that they do not require modifications of the environment.

The disadvantage is that they tend to accumulate errors without bound.

Besides these error sources, there are several other, more subtle reasons for inaccuracies in the translation of wheel encoder readings

into linear motion. All of these error sources fit into one of two categories: systematic errors and non-systematic errors.

1. Systematic Errors

Unequal wheel diameters

Average of both wheel diameters differs from nominal diameter

Misalignment of wheels

Uncertainty about the effective wheelbase (due to non-point wheel contact with the floor)

Limited encoder resolution Limited encoder sampling rate

2. Non-systematic Errors Travel over uneven floors

Travel over unexpected objects on the floor Wheel-slippage

Barshan had an extensive study of the use of gyroscopes in mobile robots [Bar95]. One of the tested instruments was the ENV-05H

Gyrostar from MURATA Co., which is the same one used in this experiment.

Fig. 2.30 shows the gyroscope, ENV-05H Gyrostar from MURATA Co. The Gyrostar is a piezoelectric vibrating gyroscope with analog voltage output that varies linearly with the measured rate of rotation, connected to a computer. However, the data acquisition of sensor data requires computer resources and memory, which diminishes the performance of the integrated system. The controller of the gyroscope developed by the author alleviates system load for multi sensor fusion [Yun99]. Fig. 2.31 shows the Gyroscope Controller and Data Acquisition Module.

Fig. 2.30 The Murata Gyrostar ENV-05H Gyroscope

Fig. 2.31 The Gyroscope Controller and Data Acquisition Module

To evaluate gyroscope characteristics, the momentary data of the gyroscope is presented in Figs. 2.32 and 2.33. The experiment was performed in the laboratory and it shows the variation of the gyroscope’s output as a voltage signal. These data show that the gyroscope has an initial voltage as a reference value (-0.15 [Volts]), and when the vehicle makes a turn, the gyroscope’s output changes [Lee95].

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Fig. 2.32 Rotate to Left Direction Test at Each Constant Velocity

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Fig. 2.33 Rotate to Right Direction Test at Each Constant Velocity