Dreamer Wishes You Happy Holidays!


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Arxiv Preprint of Our Paper on Non-Periodic Dynamic Locomotion.

We are pleased to post the submission of our paper “A Framework for Planning and Controlling Non-Periodic Bipedal Locomotion” for journal publication. The draft paper describing the framework can be found by clicking below:



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Presentations during Humanoids 2015 on Stabilizing Point Foot Biped Robots and Data Fusion

PhD student Donghyun Kim and Dr. Sentis present their experimental work on bipedal locomotion and sensing.

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Texas Tribune Festival’s Innovation Showcase

very fun day talking to attendants of the Texas Tribune Festival, discussing STEM at UT Austin, and showcasing our research on cloud to hardware funded by NASA and the Longhorn Innovation Fund for Technology.

dreamer-ut-tower  hcrl-team

greg-teleoperating-dreamer  happy-crowd-and-dreamer-ut-colors

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President Greg Fenves and Dreamer

What an honor to have UT Austin’s president and Dreamer celebrating innovation at this great university.


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Longhorn’s Innovation Fund for Technology Cloud-Based Advanced Robotics Laboratory Presentation

The focus of CARL, the Cloud-Based Advanced Robotics Laboratory, is to conduct research with robots using web browsers on mobile devices. For that, we provide a number of visualization and control tools, but most importantly the ability to gather experimental data for research.

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Undergraduate Students Control Humanoid Robot and Show hardware Creation

Bridget Owens uses the CARL web framework designed by our laboratory to conduct experiments using humanoid robots. CARL allows not only to control humanoid robots but also collect data for motion analysis. Former undergraduate student Travis Llado has created and advanced research platform. In this case, Rocky is used for studies in rough terrain manipulation and is funded by NASA Johnson Space Center.

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Three Valkyries and an MRV, and 20 years of NASA JSC ER4 history (Courtesy of NASA JSC)

Congratulations to NASA JSC for this great accomplishment. I am very happy to see the Valkyrie humanoids flourishing. I am also very proud of my lab to have helped design and build the actuators for this robot.

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History Channel’s Appearance of The Human Center Robotics Lab

Our research and some futurology are showcased in History Channel’s Ancient Aliens series.

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Oral Presentation at Dynamic Walking

Is your summer vacation a little dull? Watch our recent talk to inspire your curiosity 😉 PhD student Donghyun Kim and Dr. Sentis, present a clear explanation on whole-body control and simple motion planning to stabilize bipeds with point feet. This presentation was delivered as part of Dynamic Walking 2015 in Columbus, Ohio.

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Valkyrie at DARPA’s Robotics Challenge June 2015

This video showcases locomotion and teleoperation capabilities during demo time at the DRC finals. Valkyrie is NASA’s humanoid robot designed and built using actuator technologies from our lab.

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Hume Becomes the Biped Robot with the Smallest Point Feet to Dynamically Balance Unsupported

Using Phase Space Locomotion Planning and Whole-Body Operational Space Control, Hume becomes the point-foot biped robot with the smallest feet able to balance unsupported.

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ControlIt! Open-Source Whole-Body Control Software Framework for Humanoid Robots

We are pleased to announce ControlIt!, a new open-source software framework for Whole-Body Operational Space Control. It is offered with an LGPL v2.1 open source license. Installation and usage instructions are available here:
ControlIt! Website.The draft paper describing the software framework can be found clicking below:

Paper cover

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PhD Students Gray Thomas and Steven Jorgensen receive NASA Fellowships


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Our team receives the NASA JSC Ellite Team Award for contributions on the design of Valkyrie


On the photo below: Liang Fok, Gwen Johnson, Luis Sentis, Nick Paine

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N Steps with Phase Space Planning and Whole-Body Operational Space Control

The stabilizing properties of phase space planning in combination with the compliant SEA-based robot are shown for a N step task. Improvements on low level controllers allow the system to achieve its highest performance to date. Next improvement will be to enhance pose estimation.

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