We pioneer lifelong collaborative autonomy, creating adaptive robot teams to enhance productivity, safety, and quality of life across diverse industries.
Amherst, Massachusetts
Joined May 2020
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Sriram Siva presented his paper on "enhancing consistent ground maneuverability by robot adaptation to complex off-road terrains" at the Conference on Robot Learning (CoRL) 2021. Congratulations!
youtube.com/watch?v=6Z5cZSe3…
At RSS 2021, Peng Gao presented his paper "Bayesian deep graph matching for correspondence identification in collaborative perception" to address collaborative perception that can facilitate human-robot collaboratively assembly and connected driving.
youtube.com/watch?v=AiJ11J-S…
We brought our Spot robot to the Edgar experimental mine to test its built-in perception and navigation capabilities. Spot will be used for our lifelong collaborative autonomy research in field and subterranean robotics applications.
youtu.be/q7gfBTiVxSU
Peng Gao will also discuss his RSS paper on correspondence identification (and visual referencing) under uncertainty in collaborative perception at 9-11 am MDT (15-17 UTC) on Tuesday 7/14. Also welcome to join the discussion!
roboticsconference.org/progr…
youtube.com/watch?v=VEmWswnE…
So excited about RSS! Brian Reily will discuss his paper on multi-robot leading-following while maintaining communication at 9-11 am MDT (15-17 UTC) on Tuesday 7/14. Welcome to join our discussion!
roboticsconference.org/progr…
youtube.com/watch?v=rSBXoqBq…
Congratulations to Savannah Paul for graduating with a master's degree! Savannah did a fantastic project on designing augmented reality (AR) visualizations for synchronized and time-dominant human-robot teaming.
youtu.be/YEjxh1wM7nQ
Congratulations to @HCRoboticsLab member Brian Reily for his new paper accepted to Robotics: Science and Systems (RSS)! His paper proposes a regularized optimization method that enables robot teammates to lead a multi-agent team to multiple goals while maintaining communication.
Congratulations to @HCRoboticsLab member Peng Gao for his new paper accepted to Robotics: Science and Systems (RSS)! His paper proposes a regularized graph matching method for correspondence identification under uncertainty in collaborative perception.