PhD project title |
Energy-Conscious and Fault-Resilient Autonomous Industrial Robots via Algorithm-Hardware Co-Design
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Outline description, including interdisciplinary, intersectoral and international dimensions (300 words max) |
Industry 4.0 is a new emerging paradigm aiming at transforming the manufacturing processes by automating them through the use of autonomous robots and smart edge/cloud computing infrastructure. The operation of robots relies on a range of computationally intensive algorithms from control theory to computer vision and machine learning for autonomously moving, deciding and performing critical operations in real time. Most of these operations need to be performed under stringent power envelopes and dynamically changing environmental conditions that include varying levels of heat, electromagnetism, radiation and humidity. Such conditions make the delicate electronic processing and storage circuits prone to intermittent failures, which in turn threaten the correct functionality of robots and eventually the reliable, non-disruptive and safe, accident-free operation of factories. This project aims at addressing a truly interdisciplinary challenge by developing low cost adaptive mechanisms that enable the provably correct operation of the robot. This will be achieved through algorithm-hardware co-design that allows the adaptation of kernels typically found in robots based on feedback from the underlying hardware. To enable this we will first study the impact of potential hardware failures on such kernels using Machine Learning based failure prediction models. Task scheduling mechanisms will then be developed giving priority to critical tasks, while meeting stringent power and performance requirements. We plan to also exploit the dynamic reduction of arithmetic precision, which we have recently shown can reduce the power consumption but also the number and impact of failures on applications. The project brings together experts on low-power fault-tolerant systems, control theory and robotics and machine learning for digital manufacturing from Queen’s Electronics, Communications and Information Technology (ECIT) Global-Research-Institute, the Intelligent Autonomous Manufacturing Systems (i-AMS) Pioneer Research Programme and the Bosch Center for AI in Germany. The student will join an award winning research team in Queen’s ECIT-GRI and the i-AMS centre taking advantage of the unique infrastructure on system design, characterization, and robots while visiting Bosch in a six-month placement at the Center for Artificial Intelligence (BCAI) in Germany providing an international industrial experience. The project is expected to result in several publications in top-tier international conferences and journals venues and the ideas will be disseminated through international networks of excellence and technical committees of which the supervisors are members and through a workshop at the last year that we aim at organizing in one of the relevant top-tier international conferences.
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Key words/descriptors
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Robotics, Industry 4.0, Smart Manufacturing, Control Engineering, Software-Hardware co-Design, Fault Detection, Approximate Computing, Energy Efficient Systems, Cyber-Physical Systems, Artificial Intelligence
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Fit to CITI-GENS theme(s) |
International Elements:
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Supervisor Information
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First Supervisor: Dr Georgios Karakonstantis School: EEECS / ECIT Second Supervisor: Dr Nikolaos Athanasopoulos School: EEECS / i-AMS Third Supervisor: Dr Vien Ngo Company: Bosch, Bosch Center for Artificial Intelligence, Renningen, Germany |
Name of non-HEI partner(s) |
Robert Bosch GmbH, or Bosch, is a German multinational engineering and electronics company headquartered in Gerlingen, near Stuttgart, Germany. It is the world's largest supplier of automotive components measured by 2011 revenues. Bosch Cooperate Research: International research network of the corporate sector for research and advance engineering, comprising 12 locations in 8 countries (Palo Alto, Pittsburgh, Boston, Hildesheim, Renningen, St. Petersburg, Moscow, Bangalore, Tel Aviv, Tokyo, Shanghai, and Singapore); other engineering activities related to the development of products and services at some 120 locations worldwide. Bosch Reseach in Renningen where the fouth supervisor is based, Germany. This goal is to encourage interdisciplinary collaboration (automobile, robotic, medicine), and in this way further enhance its innovative strength. At the center of artificial intelligence in Renningen for research and advance engineering on the outskirts of Stuttgart, some 1,700 creative minds are doing applied industrial research. |
Contribution of non-HEI partner(s) to the project: |
The third supervisor, Dr Vien Ngo is a research scientist at The Bosch Center for Artificial Intelligence (BCAI). His team's research interest focuses on applying AI and ML theories for robotic manipulation. The team is in cooperation with Cyber Valley, which is Europe’s largest research consortium in the field of artificial intelligence with partners from science and industry. The state of Baden-Württemberg, the Max Planck Society with the Max Planck Institute for Intelligent Systems, the Universities of Stuttgart and Tübingen, as well as Amazon, BMW AG, Daimler AG, IAV GmbH, Dr. Ing. h.c. F. Porsche AG, Robert Bosch GmbH, and ZF Friedrichshafen AG are the founding partners of this initiative. He received the B.S. degree in Computer Engineering from Hanoi University of Science and Technology, Vietnam, in 2005, and the Ph.D degree in Computer Engineering from Kyung Hee University, Republic of Korea, in 2009. He was a postdoctoral researcher at the National University of Singapore from 2009 to 2011, at the Ravensburg-Weingarten University of Applied Sciences in Germany from 2011-2013, and a group leader at the Machine Learning and Robotics lab at the University of Stuttgart from 2013-2017. His research interests include Machine Learning, and Robotics.
Dr Ngo will continuously provide mentoring on the project part that requires formal analysis, and subsequently co-design, of ML and AI algorithms in learning of robots, and host the student in the BCAI labs. Specifically, he will 1) jointly co-supervise the student during the whole PhD project; 2) Host the student to his research group for a 6 month period in the duration of the project; 3) allow access and testing to specialized Franka industrial robot systems of the lab, used for logistics and manipulations; 4) advice on the use of ML methods for failure prediction and robotic manipulation. |
Profile of the non-HEI partner and the nature of the relationship.
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The Bosch Center for Artificial Intelligence was founded in early 2017 to deploy cutting-edge AI technologies across Bosch products and services creating solutions for industry related problems. It hosts 1700 researchers in various interdisciplinary fields including AI-based dynamics modeling, Explainable Deep Learning, Control through Reinforcement Learning and Dynamic multi-agent planning. The student will have the opportunity to gain significant practical knowledge during his placement on industrial research, and he will also be exposed to challenging industry relevant problems. |
Research centre / School |
ECIT Institute and i-AMS centre |
Subject area |
Computer Science, Electrical Engineering |