CORE Robotics Lab
@core_robotics
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The Cognitive Optimization and Relational Robotics Lab at the Georgia Institute of Technology, focusing on research in all things robotics and optimal learning.
Joined January 2020
Big congratulations to our very own Zulfiqar Zaidi for winning the “Most Cited First Author Paper” award from Georgia Tech’s Woodruff School of Mechanical Engineering! 🏆📄 Your hard work and impact are truly inspiring! 🎉
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Want to learn more about advances in agile robots?🦾🤖Make sure to check out this exciting workshop at #ICRA25!
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Out some of their latest work, see these papers: -Diffusion for multi-agent systems: https://t.co/GYPWTZIwZS -Diffusion for robotics https://t.co/ZKIcNtDVqt -VLMs for CAD Code Design: https://t.co/cF8M3Okz0w -LLMs for Alignment in Planning https://t.co/fYyH3EYE4g
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Delighted to cap this year off holding @Seancye and @Pradyumna_T. Their legacy for the @core_robotics is immense, pioneering work on generative AI (diffusion models and LLMs). Your leadership will be missed. @zoox and Toyota Research Institute are lucky to have you! To check…
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How can everyday users teach robots to perform complex, long-horizon tasks (e.g., meal prep) without relying on robotics experts for help? Our latest study published in #IJRR tackles this challenge, paving the way for more accessible human-robot collaboration. A 🧵...
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Congrats to CORE Lab member Manisha Natarajan for having her abstract titled "Adaptive Agents for Mixed-Initiative Human-AI Collaboration" accepted to @RealAAAI 2025! She will be presenting her work at the poster session in February!🤖🎉
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@core_robotics Congrats to Sam Yi Ting, Dr. Erin Botti, and Manisha Natarajan from the @core_robotics who are tremendous researchers and who helped me pursue this @NASA Early Career Funded research. 6/6 @GTrobotics @gtcomputing
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In future work, the @core_robotics will be developing adaptive robots that adjust to human stress levels and modulate workload to max performance in safety-critical settings. Here's an AAMAS'24 paper showing one way to modulate latent human variables: https://t.co/z2CxGw6FMB 5/n
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The *right* kind of stress can boost performance (to a point) while workload degrades it. Stress actually has 2 components: distress and eustress, which have differential effects. Overall, our results show that AI systems need to dynamically adapt based on all these factors. 4/n
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24 participants, multiple stress (s) and workload (w) conditions. The result? 70% performed better under moderate stress -- predicted in rat studies by the Yerkes-Dodson Law (YDL). However, performance declined as workload increased. 3/n
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Robot teleoperation is vital in safety-critical applications, such as space exploration and surgery. Understanding how stress and workload impact performance can drive safer, more efficient systems. 2/n c.f. https://t.co/HzKOkpS0aT
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Can stress improve human performance in robot teleoperation? We found that moderate stress enhances effectiveness in critical tasks, but high workload? It takes a toll. Let’s dive into the findings...🧵1/6 Link: https://t.co/VVvJ13HsTM
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“Trust and Dependence on Robotic Decision Support” has been published in @IeeeTro! Available here: https://t.co/cezaiWvgwU Bravo to Manisha Natarajan on her strong experimental work to inform how we design for appropriate trust in robotic systems. @core_robotics
ieeexplore.ieee.org
This article investigates people's trust and dependence on robotic decision support systems (DSSs), which provide cognitive assistance through suggestions. Robotic DSSs may not always offer optimal...
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@mlatgt @gtcomputing @GTrobotics Interested in how else diffusion models can be leveraged for robot model learning? Check out more papers by @Seancye et al. from @core_robotics. Check them out: https://t.co/ZKIcNtDnAV
https://t.co/GNQnEkttVb
https://t.co/uSJQqw4rRa
arxiv.org
Advances in robot learning have enabled robots to generate skills for a variety of tasks. Yet, robot learning is typically sample inefficient, struggles to learn from data sources exhibiting...
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Diffusion models can forecast trajectories, which can help with predicting aircraft flight paths to helping robots generate motion plans in complex environments. Check out our latest work on this topic that Dr. Sean Ye presented #IROS2024! Teaser Talk: https://t.co/lghcYIcmPm
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We are hiring tenure-track faculty in Robotics, HRI, AI/ML, and Graphics at @ICatGT! I am grateful for the collaborative, supportive ecosystem of amazing faculty and students in @ICatGT and strongly encourage you to apply to join us! https://t.co/qS8UavRA06
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Wishing these two CORE Lab members the best of luck with their careers!🌟We can’t wait to see what you achieve next. Congratulations once again!
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Congrats to Dr. Sean Ye and Dr. Pradyumna Tambwekar on defending their PhDs on "Trajectory Modeling using Generative Approaches for Scheduling, Planning, and Multi-Agent Systems" and "Human-Centered Specification and Explanation for Mixed-Initiative Interactions", respectively!🎉
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This work was developed in collaboration with @EsiSeraj, @rohanpaleja27, @MatthewGombolay, @zahi_kakish, and Luis Pimentel, Kin Man Lee, Zheyuan Wang, Daniel Martin, Matthew Sklar, and John Zhang.
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Finally, we demonstrated our framework on the Robotarium platform with real robots. Our HetNet-based agents coordinated seamlessly, detecting and extinguishing fires through effective communication and teamwork. Check out the demo in our paper. (8/8) Link: https://t.co/TOApK3lP2Q
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