Pranjali Padghan is a Software Engineer at Nanotronics. She holds a Master's degree in Aerospace Engineering from Pennsylvania State University. Her Master's research was focused on Dynamics and Control Systems. She has used algorithms like Model Predictive Control in obstacle avoidance and trajectory tracking for Quadcopters. Her current interests include hardware-software integration and robotics control.
Practical Integration of Artificial Intelligence to Physical Robotic Systems
The advent of Artificial Intelligence and the continued advancement of Deep Learning, Machine learning and other advanced methods has been a watershed in technological development of data processing and decision making. Images can be analyzed with greater precision and accuracy than ever before. Spoken words – from just about any language – can be translated in an instant and converted to text, machine analyzed and processed. But these achievements have been of limited application to physical systems. Autonomous cars and other symbols of technological advancement receive associations with Artificial Intelligence, the focus of the technology is on processing – data analysis – sensor interpretation and not on the integration of AI with the hardware of the automobile. This integration is vital to the advancement of closed-loop systems and allows for motor control, feedback and other sensor feed systems to take full advantage of AI resources. In this talk, we explore the current state of AI for control systems and present a case study of integration for inspection systems, which is the core of many industrial processes.