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Zeus AutoDrive

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Wednesday November 25th, 2020

ICYMI: The IROS2020 presentation for our RA-L paper. We learn robot parameters for trajectory estimation in a Gaussian variational inference setting. Our method works without ground truth, i.e. with only noisy measurements including outliers
Paper: www.dynsyslab.org/wp-content/papercite-data/pdf/wong-ral20b.pdf
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Wednesday October 7th, 2020

How is robotics being used to in the era of COVID-19? The University of Toronto Robotics Institute's faculty have produced a white paper regarding the role of Robotics in the pandemic response and beyond.

arxiv.org/abs/2009.08577
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How is robotics being used to in the era of COVID-19? The University of Toronto Robotics Institutes faculty have produced a white paper regarding the role of Robotics in the pandemic response and beyond. 

https://arxiv.org/abs/2009.08577

Thursday October 1st, 2020

Congrats to our self-driving car team, aUToronto, for placing first in the 3rd year of the SAE International AutoDrive Challenge! And on winning overall in the 3-year competition! ... See MoreSee Less

Thursday October 1st, 2020

By exploiting differential flatness and the properties Gaussian Processes, we develop a learning-based controller that achieves high-accuracy tracking while guaranteeing safety. Find our upcoming LCSS paper: ieeexplore.ieee.org/document/9140024 ... See MoreSee Less

By exploiting differential flatness and the properties Gaussian Processes, we develop a learning-based controller that achieves high-accuracy tracking while guaranteeing safety. Find our upcoming LCSS paper: https://ieeexplore.ieee.org/document/9140024
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University of Toronto Institute for Aerospace Studies