4.5.23-AI-Sze

Conference Video|Duration: 33:28
April 5, 2023
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    A broad range of next-generation applications will be enabled by low-energy autonomous vehicles including insect-size flapping wing robots that can help with search and rescue, chip-size satellites that can explore nearby stars, and blimps that can stay in the air for years to provide communication services in remote locations. Autonomy capabilities for these vehicles will be unlocked by building their computers from the ground up, and by co-designing the algorithms and hardware for autonomy and navigation. In this talk, I will present various methods, algorithms, and computing hardware that deliver significant improvements in energy consumption and processing speed for tasks such as visual-inertial navigation, depth estimation, motion planning, mutual-information-based exploration, and deep neural networks for robot perception. We will also discuss the importance of efficient computing to reduce carbon emissions for sustainable large-scale deployment of autonomous vehicles. Much of the work presented in this talk was developed in the Low-Energy Autonomy and Navigation (LEAN) interdisciplinary group at MIT (http://lean.mit.edu.ezproxy.canberra.edu.au), which is co-directed by Vivienne Sze and Sertac Karaman.
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    A broad range of next-generation applications will be enabled by low-energy autonomous vehicles including insect-size flapping wing robots that can help with search and rescue, chip-size satellites that can explore nearby stars, and blimps that can stay in the air for years to provide communication services in remote locations. Autonomy capabilities for these vehicles will be unlocked by building their computers from the ground up, and by co-designing the algorithms and hardware for autonomy and navigation. In this talk, I will present various methods, algorithms, and computing hardware that deliver significant improvements in energy consumption and processing speed for tasks such as visual-inertial navigation, depth estimation, motion planning, mutual-information-based exploration, and deep neural networks for robot perception. We will also discuss the importance of efficient computing to reduce carbon emissions for sustainable large-scale deployment of autonomous vehicles. Much of the work presented in this talk was developed in the Low-Energy Autonomy and Navigation (LEAN) interdisciplinary group at MIT (http://lean.mit.edu.ezproxy.canberra.edu.au), which is co-directed by Vivienne Sze and Sertac Karaman.
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