Francois du Plessis

The objective of this paper is to
present a unified gyro error model. The fibreoptic
gyro (FOG) will be used as the gyro
of example, but with a small adjustment the
model could be used for low-cost gyros as
well. The error model will be used in the
simulation of gyro measurements and for the
compensation of the raw FOG measurements
inside an Inertial Measurement Unit (IMU).
Such a unified error equation is needed
as most FOG design specifications and development
documentation define the system
performance parameters in the format of the
IEEE Std 952-1997 [1]. The correspondence
between this format and the more widely
published gyro error models is not obvious.
This paper will attempt to bridge this gap.

This paper outlines the design strategy for the
University of Johannesburg’s (UJ’s) hybrid vehicle entry into
the South African Solar Challenge (SASC) 2010. The SASC is
a biennial event focused on alternative energies and showcasing
various automotive technologies. The SASC is broken up into
different classes; UJ entered in the Greenfleet Technology class.
This paper presents the design principles and strategies used to
implement a working prototype vehicle which is hybrid (propelled
by multiple energy sources) and autonomous (able to operate
without human assistance).
Various specifications of the vehicle structure and systems (brakes
and steering) are discussed in the context of these two goals.
A description of physical considerations outlines the different
design decisions made in order to provide the vehicle with its
autonomous and hybrid capabilities; the design and implementation
of these systems are also described. The autonomy system
allows the vehicle to follow the path of a lead vehicle. The energy
management system implemented on the vehicle dynamically
optimises the amount of fuel used by the internal combustion
engine of the vehicle.
The vehicle produced at UJ was able to participate in the
SASC 2010 and win the Greenfleet Technology class. The vehicle
platform has allowed the development and demonstration of
hybrid energy systems and autonomous control.

This paper presents a guide on how to obtain a local
map from a SICK LMS291 laser range finder (LRF). The type of
local map produced is a feature map, where the objects (or
features) in the world are represented by line segments. Much
research has been done on local maps and how they are created
with a LRF. However, there is usually a fundamental link
missing on the hardware setup (and software commands) to allow
a local map to be produced in a real world situation from a SICK
LMS291 LRF. A design principle is therefore produced, which
consists of two main aspects. The first aspect is a hardware
setup, which uses off the shelf components to allow the SICK
LMS291 LRF to operate at a baud rate of 500 000 baud. At a
rate of 500 000 baud the LRF is able to return the highest
possible resolution scan of its environment. The second aspect
are the steps to implement a line extraction algorithm, which
allows one to fit line segments to offline data sets and to data
points extracted from the LRF in real time.

The aim of the paper is to present a method for evaluating
brushless DC motors (BLDC) for fixed wing Unmanned
Aerial Vehicles (UAVs). Selection of a BLDC motor, which
operates in its efficient region for a UAV platform’s specifications,
will affect the endurance capabilities of the UAV platform. A
four-constant model is presented as a means of modelling and
predicting the characteristics of BLDC motors. Further, physical
testing of each motor is performed on a constructed motor test
bench. Validation of the model’s results is compared to physical
testing. The methods presented provide a means of accurately
characterising a given BLDC motor. This data can be used to
design the additional components used in the UAV’s propulsion
system.

The objective of this paper is to present an alternative calibration technique for a Fiber Optic Gyroscope (FOG). Emphasis is placed on the use of neural networks to aid in the calibration process. The main objective is to reduce the cost of the calibration process by reducing the required time on a 3-axis rotation table and the amount of engineering time required to process the data. An innovative approach is also presented where the calibration is performed on the level of the sensor (gyro) instead of being performed on the system (Inertial Measurement Unit (IMU)) level. The new calibration methodology is presented and simulation results supporting the new concept is presented.