NUS Institute of Systems Science

NICF- Spatial Reasoning From Sensor Data (SF)

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About the course

Spatial sensing and reasoning technology has been used for niche enterprise and industrial applications, such as mapping and urban planning, robotic navigation, for several years. This technology has caught on in recent years and found a wide range of application markets that include automotive, consumer, industrial, and many others.

This course presents the both fundamental technology of spatial reasoning from sensor data, and practical skills and strategies for real-world applications through workshop sessions.

In this 3-day course, it covers the fundamental principles of spatial sensing technology, such as scene representation, scanning and mapping, and spatial reasoning from sensor data, as well as practical workshop sessions that allow participants to simulate and implement hands-on spatial sensing and reasoning techniques.

This course is part of the Artificial Intelligence and Graduate Certificate in Intelligent Sensing Systems Series offered by NUS-ISS.

Key Takeaways

Upon completion of the course, students will be able to: * Acquire the fundamentals of spatial sensing and spatial reasoning technology, including scene representation, scanning and mapping, spatial reasoning using feature-based approaches and the state-of-the-art machine learning based approaches. * Apply critical analysis, evaluation and synthesis to a wide range of spatial sensing and spatial reasoning problems. * Build spatial sensing and spatial reasoning systems in diverse areas such as robotics and augmented reality.

What Will Be Covered

This course will cover:

Day 1 * Introduction to spatial sensing and reasoning from sensor data * Spatial sensing: 3D sensor data representation and modelling * Workshop on 3D sensor data representation and modelling, such as constructing 3D scene map based on image/video captured by the camera.

Day 2 * Spatial reasoning: Scanning, mapping, localization * Workshop on scene mapping and localization from sensor data, such as building a camera-based localization system for place recognition.

Day 3 * Spatial reasoning: Object and scene recognition * Case studies and workshop on design and build a spatial reasoning system, such as building a vision-based inspection system for building defect inspection and inventory checking in warehouse. * Final written assessment test.

Who should attend

  • Software Developers and Engineers who need to build spatial reasoning system, such as mapping and localization system for indoor and outdoor logistic warehouse applications.
  • Data scientists who require spatial reasoning skill to analyze 3D sensor data.
  • Product managers who need to initiate and manage projects and products related with spatial reasoning.
  • Solution architects who need to integrate spatial reasoning capabilities into their intelligent sensing solution.
  • Robotic system managers who use 3D vision to improve spatial reasoning performance of their robotic system.

Trust the experts

Tian Jing

Tian Jing currently lectures in the Analytics and Intelligent Systems Practice in the areas of artificial intelligence, data analytics, and machine learning. He received his Ph.D. degree from School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Prior to j...


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