Area: Embedded Systems and Robotics Team: Wireless Localization
This site describes an alternative approach: JOP (a Java Optimized Processor) isa hardware implementation of the JVM with predictable execution time for embedded real-time systems.
Area: Embedded Systems and Robotics Team: TBD
Erich F. Haratsch is Director of Engineering at Seagate Technology, where he is responsible for the architecture of flash controllers. He leads the development of hardware and firmware features that improve the performance, quality of service, endurance, error correction and media management capabilities of solid-state drives. Earlier in his career, he developed signal processing and error correction technologies for hard disk drive controllers at LSI Corporation and Agere Systems, which shipped in more than one billion chips. He started his engineering career at Bell Labs Research, where he invented new chip architectures for Gigabit Ethernet over copper and optical communications. He is a frequent speaker at leading industry events, is the author of over 40 peer-reviewed journal and conference papers, and holds more than 100 U.S. patents. He earned his M.S. and Ph.D. degrees in electrical engineering from the Technical University of Munich (Germany).
Eshan Singh received an ScB in Electrical Engineering, along with an AB in Economics, from Brown University in 2009. After completing an MS in Electrical Engineering from Stanford in 2011, Eshan spent three years at Intel as a Component Design Engineer. Eshan returned to Stanford in 2014 and is currently a PhD candidate in the Stanford Robust Systems Group with interests in VLSI design, 3-D integrated circuits, computer architecture, validation and debug. His current research focuses on addressing challenges in validation and debug, specifically aiming to improve bug localization, increase automation and reduce debug time.
Education Materials for Embedded Systems - 12/2013
Abstract :- While the last two decades have seen revolutions in computing and communications systems, the next few decades will see a revolution in the use of every-day robotics and artificial intelligence in broad societal applications. Examples of such systems include sensor networks, the smart power grid, self-driven cars and autonomous drones. Such systems are driven by signal processing, control and learning algorithms that process sensor data, actuate control functions and learn about the environment in which these systems operate. The trustworthiness and safety of such systems is of paramount importance and has significant impact on the commercial viability of the underlying technology. As a consequence, anomalies in system operation due to computation errors in on-board processors, degradation and failure of embedded sensors, actuators and electro-mechanical subsystems and unforeseen changes in their operation environment need to detected with minimum latency. Such anomalies also need to be mitigated in ways that ensure the safety of such systems under all possible failure scenarios. Many future systems will be self-learning in the field. It is necessary to ensure that such learning does not compromise the safety of all human personnel involved in the operation of such systems.
Embedded Systems in Automotive Controls - 12/2012
Energy Harvesting for Embedded Systems - 12/2007
Paper: Sravanthi Chalasani and James M. Conrad,,"Proceedings of the IEEE SoutheastCon, Huntsville, AL, April 2008, pp. 442-447.
Embedded System design, Embedded Controls, Automation and Robotics.
Idaho State University, hairspr(but cbe any) a Carnegie-classified doctoral research and teaching embedded systems thesis institution founded in 1901, attracts students from around the world to its Idaho.