We pioneer lifelong collaborative autonomy, creating adaptive robot teams to enhance productivity, safety, and quality of life across diverse industries.
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!
https://t.co/jpWDtBvYSg
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.
https://t.co/cU0w7RsyiD
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.
https://t.co/oAOjlXEAXc
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!
https://t.co/X4vVRmIlhz
https://t.co/1gHXlPPJwe
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!
https://t.co/y8dWnaeaHt
https://t.co/OQzkgSGl2s
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.
https://t.co/1ruaaRTX2r
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.