Topic - Tele-robotic deep learning
Internet of Things and Security 
Search and rescue operation during the aftermath of disasters / accidents is a race against time. Hazardous obstacles e.g. falling debris, high temperature, radiation leak, etc pose significant hindrance to human rescuers. The unique challenges give rise to increasing wider deployment of robotic platforms. 
In this workshop, you will learn to build a robotic platform capable of scanning, mapping and exploring an unknown environment through either self- or remote-controlled navigation. Through deep learning techniques, the robotic platforms can help to identify objects in the environment and enable the human operators to make crucial decision.

Detailed learning outcomes 
  • Design and build circuits using various sensors (ultrasound, infrared, Lidar, temperature, light, humidity, etc), actuators (motors, sound, light, etc) and microcontrollers.  
  • Design and build a self-navigating robot using the sensors, actuators and microcontrollers in part i). 
  • Build secure network links over the cloud to control the robots, and to relay back sensor and image data. 
  • Build deep neural networks using industry standard tools like Tensorflow and to visualize the neural networks using tools like Tensorboard. 
  • Produce meaningful analytics and pattern information using the deep learning tools and data relayed back by the robots. 

Professor Colin TAN 
Department of Computer Science, School of Computing, NUS 

Prof Tan received his Ph.D. degree in Computer Science from the National University of Singapore. He has taught classes on embedded systems design, control system design, real-time operating systems, and mobile applications development. He has conducted research on unmanned aircraft for over 10 years in NUS. 

His research is in autonomous control of Unmanned Aerial Vehicles, and has publications in prestigious conferences like the Guidance and Navigation Conference held by the American Institute of Aeronautics and Astronautics, and the International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 

Professor SOO Yuen Jien 
Department of Computer Science, School of Computing, NUS 

Prof Soo received the B.Sc., M.Sc. and Ph.D degree from NUS in year 2000, 2001 and 2006 respectively. He has since enjoyed teaching for 10 plus years to receive numerous teaching awards such as NUS Annual Teaching Excellence Award (2012/13, 2010/11, 2007/08), NUS Annual Teaching Excellence Award Honor Roll (2014); Faculty Teaching Excellence Award (2009/10, 2008/09, 2007/08, 2006/07); Faculty Teaching Excellence Award Honor Roll (2009/10). He has been inducted to the NUS Teaching Academy in 2012. His research interests are in computer organization and computer architecture. 

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