We are organizing a workshop at #RSS2024 on Semantics for Robotics: from Environment Understanding and Reasoning to Safe Interaction. Check out the Call for Papers below

Workshop Website: lnkd.in/gEepi2Gx
CMT Submission Page: tiny.cc/RSS24SfR
Initial Submission: May 15, 2024, 11:59 pm AoE
Author Notification: May 31, 2024 ... See MoreSee Less

Exciting opportunities for MSc students! If you are in robotics or a related field, consider joining our lab for a 6-month Master’s thesis diving into cutting-edge robotics research.
Visit our webpage for more info ce.cit.tum.de/lsy/open-positions/open-research-projects/ and apply at tiny.cc/lsy-project-application

Angela Schoellig ... See MoreSee Less

Are you studying at #TUM and interested in machine learning and control for robotics? We will offer four Master-level courses for the next summer semester. Check out our website for more details ce.cit.tum.de/lsy/teaching/

Angela Schoellig ... See MoreSee Less

We have returned from our first lab retreat in February in Eibsee, Grainau (GER). It was both productive and fun, with the Toronto team virtually joining the discussions. Looking forward to an energetic year ahead of us!
Angela Schoellig University of Toronto Engineering ... See MoreSee Less

For 3rd-year UofT Eng and CS students, we have an exciting PEY (Professional Experience Year) opportunity! Join our cutting-edge robotics and AI lab in Munich and apply now!🔬See the UofT ECC portal (Job ID: 44642) www.uoftengcareerportal.ca/ Application deadline: November 15, 2023
Angela Schoellig University of Toronto Engineering ... See MoreSee Less

Only 10 days to go until #IROS2023 in Detroit! Here is where you can find us

Sun. Oct. 1 at 14:00: Prof. Angela Schoellig's talk "Safe Learning in Robotics: From Learning-based Control to Safe Reinforcement Learning" at the workshop on Formal methods techniques in robotics systems: design and control. Room 140E.

Mon. Oct. 2 at 09:24: Sepehr Samavi will present "Does unpredictability influence driving behavior" in Imitation Learning, Room 330B. Paper: lnkd.in/dFyVdutm

Tue. Oct 3 at 08:42: Wenda Zhao will present "Uncertainty-Aware Gaussian Mixture Model for UWB Time Difference of Arrival Localization in Cluttered Environments" in Localization III, Room 320. Paper: lnkd.in/d2FsYpWg ... See MoreSee Less

We analyzed 6 years of data across machine learning, robotics, and control. The verdict: high-impact research is linked to open-source success. Read our latest work on reproducibility arxiv.org/abs/2308.10008 and submit to our associated workshop at CDC2023 tiny.cc/rnw9vz
Angela Schoellig Technical University of Munich University of Toronto Engineering ... See MoreSee Less

FACT: Only 2.6% of papers at CDC 2021 included open-source code 😱

We are organizing a workshop on “Benchmarking, Reproducibility, and Open-Source Code in Controls,” to be held at the IEEE Conference on Decision and Control (CDC) 2023 on December 12, 2023. We are calling for short 300-word abstract submissions on opinions/experience in improving accessibility and reproducibility of research in control through benchmarks, open source code, software/hardware platforms, and pertinent educational content.

Topics of interest include but are not limited to:
– Any open-source implementation of control algorithms
– Any benchmarks and comparisons of control approaches, or competitions
– Tools and software/hardware platforms that enable accessible and reproducible research
– Tutorials/lectures on reproducible research best practices and standards
– Educational resources to make control theory accessible

By bringing together researchers in these topics, we aim to improve the accessibility, reproducibility, comparability, usability, and visibility of research in control theory. We look forward to your contributions!

Submission link: tiny.cc/cdc23-ws-abstract
Deadline: September 18, 23:59 PST
Format: Accepted abstracts will be presented as lightning talks at the workshop

Angela Schoellig Technical University of Munich University of Toronto Engineering ... See MoreSee Less

Simultaneous localization and mapping (SLAM) with online scene change detection is very important for long-term robot deployment, as failing to detect such changes can lead to localization drifts, inaccurate maps and lost robots. However, current approaches focus on high dynamics that can be observed in consecutive frames, failing to handle long-term, incremental changes.
In our recent works accepted at #RSS2023, we tackle this challenge in semi-static environments, introducing POV-SLAM. We show that our probabilistic, object-aware method produces more stable robot pose estimates and more consistent scene reconstructions despite the scene changing significantly over time. We summarize our contributions as follows:
We propose a bimodal measurement likelihood for potentially-changing objects and derive its evidence lower bound (ELBO) for efficient inference
We design an online, object-aware SLAM framework using an Expectation-Maximization algorithm and the proposed measurement model to track incremental scene changes
We release a real-world long-term SLAM dataset captured in a warehouse over a four-month span
Thank you to Clearpath Inc, Natural Science and Engineering Research Council of Canada (NSERC), and Vector Institute for supporting our research. We look forward to seeing everyone at #RSS2023!
Check out our paper and dataset for more details.
Paper: arxiv.org/abs/2307.00488
Dataset: github.com/Viky397/TorWICDataset#The-Toronto-Warehouse-Incremental-Change-SLAM-Dataset ... See MoreSee Less