Complex Systems
Dr David Austin has over 15 years' experience with robots, which are arguably the most complex systems in existence. A robot consists of a mix of sensors, computers and actuators. This makes robots a distributed system, with complex interactions between the timing of sensor measurements and actuation. Typical sensors include laser range scanners, video cameras (computer vision), ultrasonic range sensors and optical encoders to measure wheel movements and joints angles. Actuators are typically controlled using pulse width modulation (PWM), by an embedded microcontroller. Dr David Austin has extensive experience with all aspects of robot design, constuction and control. He also lead the developement of an open-source robot control system, consisting of over 500,000 lines of code. Robots are also particularly complex because they deal with an unpredictable physical environment.
One of the key challenges facing most complex, autonomous systems today is dealing with uncertainty. Usually uncertainty arises due to the impact of the environment on the system. For example, measurements of the environment are always affected by random noise, to a lesser or greater degree. Often, the result is that aggregated measurements are conflicting, and cannot be reconciled without sophisticated tools. MadJ Innovations is expert in using statistical methods, and particularly, computational statistical tools to combine uncertain measurements in order to model the environment of a complex system.
Dr David Austin, director of MadJ Innovations, has extensive experience in all kinds of hardware and software systems. He has over 25 years' programming experience, over 20 years' electronics experience and over 15 years' experience with complex systems with multiple hardware and software components. He has experienced and debugged all kinds of problems due to distributed systems with race conditions and deadlocks due to resource contention. Dr David Austin is experienced with all types of communication between distributed components of a complex system.
