Introducing our work on control of liquid cooled viscoelastic bipedal robots. Apptronik developed for UT Austin this excellent humanoid lower body robot, dubbed DRACO, and students at UT’s HCRL lab devised actuator control algorithms and integrated Time-to-Velocity Reversal Locomotion and Whole-Body Locomotion Control algorithms. The result is unsupported dynamic balancing of DRACO. A link to the paper preprint is here (click on the image):
HCRL students, alumni and friends having a good time after presenting and giving a talk at ICRA 2019.
Our lab just returned from ICRA 2019 where we had a terrific time. We’re sharing a video of the talk at the workshop on legged robots: https://icra2019wslocomotion.wordpress.com/program
Apptronik and the Human-Centered Robotics Lab at UT Austin have joined forces to develop a force augmentative exoskeleton called Sagittarius. The video shows a subject wearing a 12 degree-of-freedom human-interactive and high-power density lower-body exoskeleton developed by Apptronik. A whole-body augmentative exoskeleton control algorithm has been jointly developed, allowing the exoskeleton to remove gravitational payload while standing or walking.
B. He, H. Huang, G.C. Thomas, L. Sentis, Complex Stiffness Model of Physical Human-Robot Interaction: Implications for Control of Performance Augmentation Exoskeletons, Submitted, 2019
R. Schlossman, M. Kim, U. Topcu, L. Sentis, Toward Achieving Formal Guarantees for Human-Aware Controllers in Human-Robot Interactions, Submitted, 2019
This work explores the use of formal methods to construct human-aware robot controllers to support the productivity requirements of humans. We tackle these types of scenarios via human workload-informed models and reactive synthesis. This strategy allows us to synthesize controllers that fulfill formal specifications that are expressed as linear temporal logic formulas.
Here, we advance on real-time grasping pose estimation of single or multiple handles from RGB-D images, providing a speed up for assistive human-centered behaviors. We propose a versatile Bayesian framework that endows robots with the ability to infer various door kinematic models from observations of its motion. Combining this probabilistic approach with a state-of-the- art motion planner, we achieve efficient door grasping and subsequent door operation regardless of the kinematic model using the Toyota Human Support Robot.
arXiv Preprint: M. Arduengo, C. Torras, L. Sentis, A Versatile Framework for Robust and Adaptive Door Operation with a Mobile Manipulator Robot
Click below to view the PDF of our work titled: Dynamic Locomotion For Passive-Ankle Biped Robots And Humanoids Using Whole-Body Locomotion Control.
Mercury achieves versatile dynamic walking including rough terrain. Congratulations to postdoc Donghyun Kim!
We’re delighted to share that our 2016 paper ControlIt!, is the 5th Most Read paper on IJHR and our 2005 and 2004 IJHR papers on Whole-Body Control are the 3rd and 4th Most Cited papers of IJHR!
Former PhD student Ye Zhao, now an assistant professor at Georgia Tech submitted a comprehensive paper on task and motion planning in collaboration with the Human Centered Robotics Laboratory. Click on the image below to access the paper in arXiv.
The video was made by Seeker. Click on the image below to see it.
Home robots are closer than what we may think. The video below is collaborative research under the UT Austin Villa team for qualifying for RoboCup@Home 2019. More to come soon!
