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The new Dreamer/Meka compliant humanoid robot
Series Elastic Actuator of Hume
Slides from Humanoids 2011
Illustrations of the Hume Biped for Fast Locomotion in Irregular Terrains
UT Austin’s biped robot for fast rough terrain locomotion. The Hume biped will be capable of maneuvering on terrains with height variations between 0-40 [cm] at speeds above 1 [m/s]. It uses SEA actuators with joint velocities above 10 [rad/s] and joint torques above 100 [Nm]. Its overall weight is 15 [Kg] and its overall height is 1.6 [m] thus resembling a mid size person.
Motion Planning of Extreme Locomotion Maneuvers, Humanoids 2011
The HCRL on YNN TV Channel at Barnes & Noble
Kids in North Austin had a sneak peek at the future Saturday. Saturday, the Barnes & Noble story in the Arboretum hosted Dreamer, an artificially intelligent humanoid robot. Dreamer’s brain was programmed by the scientists at UT’s Human Centered Robotics Lab. One of those scientists, Dr. Luis Sentis, was on hand to demonstrate what the robot can do. His work deals mostly with force augmentation, which looks into how robots can help to augment the movements of humans. The event had future roboticists in mind. Money from coffee and books sales will go to the Anderson High School Robotics Program.
Stability Analysis to Plan Dynamic Locomotion in Very Rough Terrain, IROS 2011, ISRR 2011
Master’s Project: Tricky, Force Controlled Holonomic Base
Master’s students, Somudro Gupta (demonstrator) and Pius Wong (video) show their work on design and control of our new holonomic base Tricky. Tricky employs omni wheels set in a triangular configuration to achieve omni-directional force control. It uses three Maxon motors rated at 250W with 3 stage planetary gears and 60 gear ratio providing 18Nm of torque per wheel. To control the torques, we have developed a new amplifier board capable of doing both current and load cell feedback. The board uses a Freescale 8-bit MC9S08MP16 microcontroller to achieve servo rates of 4KHz. The movie shows force interactions between the base and a user, based on servoing torque feedback.
