Case Study
Friday, June 30
04:30 PM - 05:00 PM
Live in San Francisco
Less Details
The talk will focus on designing an embedded platform that exposes the hardware and software capabilities as per a fully capable robot, so that experiences can be rapidly realized. This involves exposing the actuators over their full degree of freedom, providing sensor information through a high-bandwidth and low jitter network to the control system, baking in functional safety and security into the platform so as to mitigate vulnerabilities and hazards. The layered design of platform will be highlighted, and its network abstraction and design abstraction separation elaborated. We will wrap up with some of the tooling that enables discovery of data patterns from functional safety datasets.
Ahsan Qamar has a multidisciplinary background in control design, mechatronics, embedded systems and Model-Based Systems Engineering (MBSE). He graduated with a MSc. in Electrical Engineering from Aalborg University Denmark, followed by a PhD. in Mechatronics from KTH-Royal Institute of Technology, Sweden. He has ten years of experience in applying systems engineering (MBSE) within automotive, aerospace, robotic manufacturing and semiconductor domains. Most recently, he has been applying systems engineering and MBSE to the design of autonomous applications, especially feature delivery, system architecture, requirement maturity, and ontological foundation for digital thread/twin. In his current role as Technical Manager, he oversees system architecture and systems engineering for development of autonomy features at Ford. He is also a principal investigator on Ford’s research efforts with Georgia Tech and Clemson, focusing on visual analytics and variant management, that led to the development of tools as Datahawk, SafetyLens and DigitalLens. Dr. Qamar is an invited speaker for several systems engineering, safety and model-driven engineering conferences, and reviews research publications for many journals within these areas.