We are thrilled to announce that our paper on a smooth representation of belief over SO(3) for deep rotation learning will be presented at Robotics: Science and Systems 2020. This work was a collaboration between STARS lab members Valentin (now alumni!) and Matthew, together with Prof. Nicholas Roy, W. Nicholas Greene and Dr. David M. Rosen at MIT. Watch the 5 minute video summary below!
Several STARS lab members helped organize the Debates on the Future of Robotics Research workshop that was held (virtually) on Friday, June 5th as part of ICRA (2020). The workshop live stream received over 1100 unique viewers and was enthusiastically received by both participants and viewers! Congratulations to STARS students (and alumni) Matthew Giamou, Valentin Peretroukhin and Lee Clement, as well as Prof. Kelly, who helped organize the event!
We’re excited to have three lab papers that will be presented at this year’s (virtual) ICRA 2020 conference! Highlights and video links are below.
Check out our new extension to DPC-Net (from ICRA 2018): we show that DPC networks can be trained in a fully self-supervised manner, which improves accuracy and allows for retraining online in new environments!
Got features? Our recent RA-L and ICRA 2020 work demonstrates how to learn maximally-matchable image mappings to dramatically reduce the data needed for experience-based navigation.
Check out our work on a QCQP approach to inverse kinematics for redundant manipulators. We show that this difficult, nonconvex problem often admits a provably tight convex relaxation that can be efficiently solved! Coming soon to MoveIt!
We’re delighted to be co-organizing the RSS 2020 Workshop on Power-On-and-Go Robots: ‘Out of the Box’ Systems for Real-World Applications! More details at https://www.power-on-and-go.net/
Substantial advances have been made over the past two decades in the area of mobile robot autonomy, in part due to the development of sophisticated methods to fuse data from multiple information sources. However, these gains come with the caveat that proper system initialization and calibration are essential. Starting with or quickly discovering the “right” initial conditions for the selected estimation, planning, and control algorithms is a crucial but largely overlooked problem that has not yet been fully tackled by the community—instead it is often regarded as a post-hoc ‘engineering’ issue rather than a key safety concern, for example. In a future where robots actively operate alongside people in human environments, businesses and consumers will demand that the machines work correctly the first time, every time, anywhere, with minimal external (human) intervention.
The workshop will bring together researchers from diverse backgrounds to address topics related to power-on- and-go robots: robotic systems that are able to successfully deal with new situations fluidly and to adapt immediately to new environments or to changes in their own operating parameters.
Please consider submitting an extended abstract for presentation at the virtual workshop! The deadline has been extended and is now June 21st, 2020.
We’re excited to announce the release of our University of Toronto Canadian Planetary Emulation Terrain Energy-Aware Rover Navigation Dataset. The dataset was gathered by a small, four-wheeled rover at a planetary analog test facility in Canada. The rover was equipped with a suite of sensors designed to enable the study of energy-aware navigation and path planning algorithms. Our International Journal of Robotics Research data paper is available here.
The dataset includes more than 14,000 colour omnidirectional stereo panoramas captured from a synchronized 10-camera cluster and 16,000 high-resolution monocular terrain images. IMU, pyranometer (solar irradiance), drive power consumption, wheel encoder, and GPS measurements are also included. All data are presented in human-readable text files and as standard-format images; additional Robot Operating System (ROS) parsing tools and several georeferenced aerial maps of the test environment are also included. The full dataset is accessible from:
Congratulations to Dr. Valentin Peretroukhin for successfully defending his PhD on March 6! His dissertation, “Learned Improvements to the Visual Egomotion Pipeline” described ways to augment classical visual egomotion techniques with learned models. We wish him the best as he moves to Boston to postdoc at MIT!
We’re organizing the second ‘Debates on the Future of Robotics Research’ workshop at ICRA 2020 in Paris! The event will take place on May 31 – we have an outstanding group of speakers and organizers this year and are looking forward to a memorable day of discussions! Submissions for the Lightning Talks session are now open – full details are available at http://roboticsdebates.org/. Hope to see you there!
Congratulations to Dr. Lee Clement for successfully defending his PhD on November 29! His dissertation, “On Learning Models of Appearance for Robust Long-Term Visual Navigation” focussed on enabling successful long-term autonomy (localization, navigation, and mapping) under substantial appearance change (due to lighting variation and other effects). We wish him success in the future!
Cybersecurity is already a critical issue – what will happen when we deploy thousand or millions of (potentially hackable) robots on our roads, in our hospitals, and inside our homes? Prof. Kelly is giving a keynote talk about these issues at this year’s CANARIE Summit in Montreal on October 1!
We’re super-proud of Erin Richardson, our lab alum, who was featured with the awesome aerospace engineer, tireless STEM promoter, and UTIAS graduate Natalie Panek in “Path Among the Stars” – a short segment aired during the CNN Apollo 11 documentary film (June 23, 2019). Congratulations Erin and Natalie – you inspire us to reach for the stars!