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Zeus AutoDrive

To get updates from our aUToronto self-driving car team, please visit this page.

 

Dynamic Systems Lab News

 

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Tuesday September 8th, 2020

Want to play catch with a mobile manipulator? Why not! We proposed a planning and control framework that achieves a success rate of 85%, accepted to IROS2020.
Paper: www.dynsyslab.org/wp-content/papercite-data/pdf/dong-iros20.pdf
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Friday August 14th, 2020

Prof. Angela Schoellig presented "Safe and Efficient Active Learning Strategies for Robotics Applications" at the ICML workshop on Real World Experiment Design and Active Learning check out the video at 7:32:00!
icml.cc/virtual/2020/workshop/5745
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Prof. Angela Schoellig presented Safe and Efficient Active Learning Strategies for Robotics Applications at the ICML workshop on Real World Experiment Design and Active Learning  check out the video at 7:32:00!  
https://icml.cc/virtual/2020/workshop/5745

Wednesday August 12th, 2020

Wondering how to guarantee success in cross-robot experience transfer? Our L-CSS paper presents an approach to predict transfer performance in cross-robot model transfer and highlights the asymmetric nature of cross-robot transfer problems.
Paper: arxiv.org/pdf/2006.16126.pdf
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Monday August 10th, 2020

In our upcoming 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.

Find the paper here: www.dynsyslab.org/wp-content/papercite-data/pdf/wong-ral20b.pdf
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In our upcoming 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. 

Find the paper here: https://www.dynsyslab.org/wp-content/papercite-data/pdf/wong-ral20b.pdf

Friday August 7th, 2020

Prof. Angela Schoellig presented talk about safe learning control at the IFAC 2020 Learning for Control Tutorial along side Andreas Krause, Francesco Borrelli, and Shie Mannor. Find it below!
Tutorial Webpage: www.ifac2020.org/program/tutorials/learning-for-control/
Slides: www.dynsyslab.org/wp-content/papercite-data/slides/schoellig-ifac20-slides.pdf
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Friday July 17th, 2020

We present our perception-aware model predictive controller at the IFAC World Congress 2020. The controller accounts for camera orientation and location of visual landmarks to fly fast but reliably.
Paper: www.dynsyslab.org/wp-content/papercite-data/pdf/greeff-ifac20.pdf
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Wednesday July 15th, 2020

Want to set up your own ultrawide-band (UWB) indoor localization system? But where to put the radio sensors? Check out our work at the IFAC World Congress 2020 to help you find the optimal sensor locations.
Paper: www.dynsyslab.org/wp-content/papercite-data/pdf/zhao-ifac20.pdf
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Monday July 13th, 2020

Jacopo Panerati, postdoctoral fellow in our group, is participating in the RSS Pioneers Workshop 2020. He shares his thoughts on the gap between multi-agent deep reinforcement learning (MARL) and swarm robotics—and how to bridge it.
More Info: sites.google.com/view/rsspioneers2020/participants
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Thursday July 9th, 2020

Throwback to last year's stage of the SAE AutoDrive Challenge! Find our systems paper summarizing aUToronto's winning self-driving car design from the competition published in the Journal of Field Robotics.
Paper: arxiv.org/abs/2004.08752
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Monday July 6th, 2020

Can you localize a UAV by comparing its view with Google Earth images? We demonstrate accurate localizations of a multi-rotor UAV with a gimballed camera and an IMU using Google Earth to estimate the global pose on 7.1km of real world data with variable lighting conditions. Presented at ICRA2020
Paper: www.dynsyslab.org/wp-content/papercite-data/pdf/patel-icra20.pdf
Questions? ICRA Slack tuc07_6
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University of Toronto Institute for Aerospace Studies