The desirability and challenge of developing a completely autonomous vehicle and the rising need for more efficient use
of energy by automobiles motivate this research- a study for an optimum solution to computer control of energy efficient
vehicles. The purpose of this paper is to compare three control methods - mechanical, hydraulic and electric that have
been used to convert an experimental all terrain vehicle to drive by wire which would eventually act as a test bed for
conducting research on various technologies for autonomous operation. Computer control of basic operations in a vehicle
namely steering, braking and speed control have been implemented and will be described in this paper. The output from
a 3 axis motion controller is used for this purpose. The motion controller is interfaced with a software program using
WSDK (Windows Servo Design Kit) as an intermediate tuning layer for tuning and parameter settings in autonomous
operation. The software program is developed in C++. The voltage signal sent to the motion controller can be varied
through the control program for desired results in controlling the steering motor, activating the hydraulic brakes and
varying the vehicle's speed.
The vehicle has been tested for its basic functionality which includes testing of street legal operations and also a 1000
mile test while running in a hybrid mode. The vehicle has also been tested for control when it is interfaced with devices
such as a keyboard, joystick and sensors under full autonomous operation. The vehicle is currently being tested in
various safety studies and is being used as a test bed for experiments in control courses and research studies. The
significance of this research is in providing a greater understanding of conventional driving controls and the possibility
of improving automobile safety by removing human error in control of a motor vehicle.
History shows that problems that cause human confusion often lead to inventions to solve the problems,
which then leads to exploitation of the invention, creating a confusion-invention-exploitation cycle.
Robotics, which started as a new type of universal machine implemented with a computer controlled
mechanism in the 1960's, has progressed from an Age of Over-expectation, a Time of Nightmare, an Age
of Realism, and is now entering the Age of Exploitation.
The purpose of this paper is to propose architecture for the modern intelligent robot in which sensors permit
adaptation to changes in the environment are combined with a "creative controller" that permits adaptive
critic, neural network learning, and a dynamic database that permits task selection and criteria adjustment.
This ideal model may be compared to various controllers that have been implemented using Ethernet, CAN
Bus and JAUS architectures and to modern, embedded, mobile computing architectures. Several
prototypes and simulations are considered in view of peta-computing. The significance of this comparison
is that it provides some insights that may be useful in designing future robots for various manufacturing,
medical, and defense applications.
The purpose of this paper is to introduce a concept of eclecticism for the design, development, simulation
and implementation of a real time controller for an intelligent, vision guided robots. The use of an eclectic
perceptual, creative controller that can select its own tasks and perform autonomous operations is
illustrated. This eclectic controller is a new paradigm for robot controllers and is an attempt to simplify the
application of intelligent machines in general and robots in particular. The idea is to uses a task control
center and dynamic programming approach. However, the information required for an optimal solution
may only partially reside in a dynamic database so that some tasks are impossible to accomplish. So a
decision must be made about the feasibility of a solution to a task before the task is attempted. Even when
tasks are feasible, an iterative learning approach may be required. The learning could go on forever. The
dynamic database stores both global environmental information and local information including the
kinematic and dynamic models of the intelligent robot. The kinematic model is very useful for position
control and simulations. However, models of the dynamics of the manipulators are needed for tracking
control of the robot's motions. Such models are also necessary for sizing the actuators, tuning the
controller, and achieving superior performance. Simulations of various control designs are shown. Much of
the model has also been used for the actual prototype Bearcat Cub mobile robot. This vision guided robot
was designed for the Intelligent Ground Vehicle Contest. A novel feature of the proposed approach lies in
the fact that it is applicable to both robot arm manipulators and mobile robots such as wheeled mobile
robots. This generality should encourage the development of more mobile robots with manipulator
capability since both models can be easily stored in the dynamic database. The multi task controller also
permits wide applications. The use of manipulators and mobile bases with a high-level control are
potentially useful for space exploration, certain rescue robots, defense robots, medical robotics, and robots
that aids older people in daily living activities.