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Thread: Hume, bipedal robot for rough terrain locomotion, Human Centered Robotics Lab, Austin, Texas, USA

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    Hume, bipedal robot for rough terrain locomotion, Human Centered Robotics Lab, Austin, Texas, USA


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    Hume: The Rough Terrain Biped

    Published on Mar 24, 2012

    The Human Centered Robotics Laboratory at UT Austin and Meka Robotics, present Hume, a bipedal robot for rough terrain locomotion. Hume has been designed to achieve the skill of Human Centered Hyper-Agility (HCHA). In particular the extrema of HCHA includes free-running-like capabilities on near-vertical surfaces. HCHA is a very important capability because of its direct impact in the design of human assistive devices for all terrains and the design of next generation semi-autonomous bipedal robot. To design Hume, we conducted computational simulations of rough terrain locomotion, compared them with human subjects moving nimbly in the same terrains, designed a high performance modular Series Elastic Actuator (SEA), and built a 6 Degree of Freedom, 15 Kg biped, that can achieve 10 rad/s of angular speeds and 100 Nm of joint torques. The robot is designed for interacting with human scale environments at human like speeds. To facilitate this capability, each actuator utilizes series elastic elements for high bandwidth force sensing and rugged impact tolerance. To maintain low leg mass and allow for quick maneuvers, the actuators are located as high and near the center of mass as possible. Packed into the center of the torso are the leg abduction/adduction actuators while the hip ?exion/extension actuators ride just above the hip's center of rotation. This con?guration keeps the knee ?exion/extension actuator as the only mechanism located on the leg and thus minimizes swing inertia and provides for an overall lighter leg. Each joint of the biped is driven by a modular series elastic actuator (SEA). The design utilizes a ball screw as the major transmission component providing an ef?cient high gear reduction while maintaining a low rotational inertia. The ball screw drives a set of stiff springs that decouple impacts and provide force sensing. This whole spring assembly rides along on special linear bushings that are able to auto compensate for any misalignment thereby reducing friction. For the ?exion/extension joints, the SEA output is then attached to cables that drive the joint while the abduction/adduction actuators use push/pull rods to maneuver the leg

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    The Legend of the Drunken Robot

    Published on Aug 19, 2014

    This research is sponsored by the US Office of Naval Research. Hume uses its series elastic actuated legs to remain balanced while walking. It achieves this capability by observing the center of mass position error relative to a reference path and re-planning at every step a new reference trajectory to minimize the error. We use phase space planning techniques to plan the center of mass trajectories and foot placement. Thus, our approach is based on continuous re-planning. By planning the path of the next step based on the observed initial error, we can find the proper landing location of each step. Relying on the prismatic inverted pendulum model instead of the linear inverted pendulum model we also enable non-planar center of mass motion, which will be essential later on for rough terrain locomotion.

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    Hume Biped Robot Performing Balance on Split Terrain and Undirected Walking

    Published on Jan 9, 2015

    The first experiment, shows the Hume biped robot balancing on a high pitch split terrain with and without push disturbances. We implement a Whole-Body Operational Operational Space Controller to compute joint torques consistent with a desired set of operational space accelerations, known contact constraints, and desired internal forces. The internal forces, during multi- contact, correspond to the linear subspace of joint torques that do not cause accelerations of the robot. For undirected walking, Hume continuously steps forward and backward to remain balance. To accomplish this capability, we feed foot trajectories from an algorithm called Continuous Time to Velocity Reversal Online Planner. The planner continuously calculates new trajectories for the feet in an online fashion to recover from disturbances.

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    Towards attractor based dynamic stepping

    Published on Feb 1, 2015

    In this video we show improvements on phase-space dynamic walking based on using an absolute return frame. The description of the planner can be found at
    "Assessing Whole-Body Operational Space Control
    in a Point-Foot Series Elastic Biped:
    Balance on Split Terrain and Undirected Walking
    "

    by Donghyun Kim, Ye Zhao, Gray Thomas, Luis Sentis
    January 13, 2015

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

    Published on Feb 15, 2015

    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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    Debugging untethered walking on dynamic walking biped hume

    Published on Apr 5, 2015

    In this video, the Hume biped is able to achieve 6 steps of dynamic untethered walking using our phase space continousl planning algorithm and whole-body operational space control. With proper debugging of the velocity estimation our laboratory hopes to soon achieve N steps of untethere walking.

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    Improvements on untethered balancing with point foot robot Hume

    Published on Apr 30, 2015

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    The Legend of the Drunken Robot, Now in 3D, Continues

    Published on May 4, 2015

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    Balance planner based on Kalman filter estimation of foot positions

    Published on May 29, 2015

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