ARCO Lab
It’s been a while since we’ve posted, but the ARCO Lab team has had a busy winter! In addition to working hard on courses and research, we set up our first server, the Robotic Analysis and Intelligent Computation HUb (RAICHU) in a new lab space. At the end of the fall semester, everyone was rightfully […]
The folks at ARCO Lab were delighted to attend the 26th Midwest Optimization Meeting (MOM26) on Friday, Nov. 9th and Saturday, Nov. 10th at The University of Waterloo. As roboticists interested in applying optimization theory, we learned a great deal, including how to think about Bayesian D-optimality as a special case of a more general […]
I had the pleasure of giving a talk at the 2024 Workshop on IV Meets Urban: Safe and Certifiable Navigation and Control for Intelligent Vehicles in Complex Urban Scenarios at IEEE ITSC. It was an excellent opportunity to share ideas with researchers tackling state estimation and control problems relevant to intelligent transportation systems, autonomous vehicles, robotics, […]
ARCO Lab kicked off the fall semester with a BBQ! A big thank you to summer research students Cole, Charlotte, and Andrew for their hard work—best of luck with co-op and the new school year! We also welcomed new master’s students Hussein, Aliyah, Kiran, and Alaap. Our research focus this year is primarily on applying […]
ARCO Lab presented two posters at the Faculty of Engineering’s annual Undergraduate Summer Research Poster Showcase! Thank you to Andrew, Charlotte, and Cole for their hard work on mapping caves and creating a 2D localization simulation.
We paid a visit to Rattlesnake Point Conservation Area to collect some data! Summer student Andrew Brink led the charge with his custom helmet-mounted OAK-D Pro camera. The Niagara Escarpment is home to many crevice caves with unique characteristics and tight squeezes that make them extremely challenging to map with standard sensors and algorithms. In […]
On Wednesday, May 30th, Professor Giamou and Ethan Sequiera presented ARCO Lab’s first completely homegrown paper at the 21st Conference on Robots and Vision at The University of Guelph! We formulated the optimal placement of ranging beacons in a robot’s environment as a set function maximization problem. This allowed us to use an efficient greedy […]
Professor Giamou presented some work on leveraging equivariance for a generative approach to learning inverse kinematics for redundant manipulators at Boston Symmetry Day at Northeastern University on April 27, 2023. Check out this work in the latest version of the preprint (in collaboration with STARS Laboratory).