Developing Autonomous Systems: Perception Algorithms
Overview
Whether your robot flies, drives, swims, or manipulates, algorithms that turn sensor data into self-awareness and situational awareness will be a critical component of any autonomous system. In this webinar, you will learn how to design, implement, and test a variety of these algorithms – all using MATLAB and Simulink.
- Collecting and processing real and simulated data in MATLAB
- Applications of data for autonomy, including object/obstacle detection using AI, object tracking, sensor fusion for localization, and mapping
- Testing and deployment of perception algorithms
Please note: this series is a rerun in the Australian and New Zealand time zone and will be hosted by Australian based engineers.
About the Presenter
Julia Brault received a B.S. and M.S. from Northeastern University in Mechanical Engineering, with a concentration in mechanical design and mechatronic systems. She is a Senior Application Engineer focusing on robotics and automated systems who joined MathWorks 8 years ago in 2017.
Dr Peter Brady is a Principal Application Engineer with a background in numerical simulation, big data analysis and high-performance computing. Prior to joining MathWorks he worked at several civil and defence contractors undertaking detailed computational fluid dynamics investigations. At MathWorks Australia Peter supports the areas of: maths and statistics, machine and deep learning as well as providing an Australian based contact MathWorks’ autonomous customers to access global resources. He holds a bachelor’s degree in civil engineering and PhD in mechanical engineering. Peter is a member of Engineers Australia and is a Chartered Practicing Engineer in the fields of Civil and Mechanical Engineering as well as Engineering Leadership and Management. He is a member of the Australian Computer Society where he holds the level of Certified Professional.
Product Focus
This event is part of a series of related topics. View the full list of events in this series.
