Our students Minkyu, Nico and Arnau, will be competing at RoboCup@Home Domestic Standard Platform in Montreal this week along a larger team. Wishing the whole Austin Villa team best luck!
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Snippets of Panel at SXSW on Mobility Beyond Wheelchairs
Congratulations to Rachel for this featured article from NASA
Steven’s summer project with NASA JSC, IHMC and U. Michigan on Intuitive Whole-Body Control of Valkyrie!
This video summarizes the deployment of applications on Valkyrie performed by Steven Jens Jorgensen from the U. of Texas at Austin and other researchers at NASA, IHMC, and U. Michigan. Given desired end-effector poses, a nonlinear optimization routine is used to solve the whole-body Inverse Kinematics (IK) of NASA’s Valkyrie robot while satisfying balance constraints. The joint position solutions are converted to the appropriate messages and are sent to IHMC’s controller interface, which interpolates between the robot’s initial (current) configuration to the desired configuration using third-order functions (polynomial for positions and a hermite curve for orientations). By specifying just the hand pose, a preliminary grasp planner uses the Whole-body IK solver to command Valkyrie’s hand to the desired pose. The Whole-body work is a collaboration between NASA and the Human-Centered Robotics Lab (HCRL) at the University of Texas at Austin. The grasp planner is from The Laboratory for Progress at the University of Michigan. This work was partially supported by a NASA Space Technology Research Fellowship (NSTRF) under the grant number NNX15AQ42H.
Congrats to Students for Best Manipulation Paper Award
Congratulations to Prashant Rao from the ReNeu Lab, Gray Thomas from the Human Centered Robotics Lab, and ReNeu’s Lab PI Ashish Deshpande, for winning the IEEE ICRA 2017 Best Robotic Manipulation Paper Award!
Workshop Talk IEEE ICRA 2017
Gray, Donghyun and Luis had a blast talking about our new lab’s pet topic “Uncertainty in Human-Centered Robots” #icra2017 #singapore #marinabaysands
Abstract: Uncertainty permeates in all control approaches and significantly complicates controller design. This is specially true for human-centered robots which rely on oversimplications such as ignoring high-frequency behaviors or realtime delays to central computers. In this talk Luis will join forces with HCRL students Gray and Donghyun to present detailed mathematical work on choosing structure for measuring uncertainty in a meaningful statistical sense, motivate the nature of uncertainty in hardware systems involving high performance series elastic actuators, and devise a planning and control framework that embraces uncertainty to external disturbances via reinforcement learning of locomotion responses.
