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

[Airicist]

Developer - Human Centered Robotics Lab (https://pr.ai/showthread.php?5423)

[Airicist]

https://youtu.be/tNTU5O5urmA

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

[Airicist]

https://youtu.be/1iC7s2ub1E4

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.

[Airicist]

https://youtu.be/E01xK8CrXOo

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.

[Airicist]

https://youtu.be/v0370pBIRGU

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 (https://arxiv.org/pdf/1501.02855v1.pdf)"

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

[Airicist]

https://youtu.be/Gj7PNHTCQNA

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.

[Airicist]

https://youtu.be/vqHOOlJqvoM

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.

[Airicist]

https://youtu.be/GXrP8qQUNGw

Improvements on untethered balancing with point foot robot Hume

Published on Apr 30, 2015

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https://youtu.be/p309GTUK2eA

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

Published on May 4, 2015

[Airicist]

https://youtu.be/YEbREXRvVAc

Balance planner based on Kalman filter estimation of foot positions

Published on May 29, 2015

[Airicist]

https://youtu.be/nkk3aq6Xycs

Hume Point-Foot Biped Dynamically Balances on Smallest Feet

Published on Jun 27, 2015


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. This research has been sponsored by the US Office of Naval Research

[Airicist]

https://youtu.be/xuwrDthb_LM

Smallest point foot biped breaks own record

Published on Jul 10, 2015


With additional improvements to the calibration, sensing and control systems, the Hume biped gets the most stable dynamic balancing sequence to date.

[Airicist]

https://youtu.be/3TiuDMV6jr8

Step by step guidelines point foot unsupported walking

Published on Jul 24, 2015


PhD student Donghyun Kim, presents 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.

[Airicist]

https://youtu.be/DLfmw0yVvrk

revised video version 2

Published on Jan 13, 2016

[Airicist]

https://youtu.be/EEcQRkTLqbk

Mobility around humans with Mercury

Published on Sep 11, 2018


This video shows a human-size bipedal robot, dubbed Mercury, which has passive ankles, thus relying solely on hip and knee actuation for balance. Unlike humans, having passive ankles forces Mercury to gain balance by continuously stepping. This capability is not only very difficult to accomplish but enables the robot to rapidly respond to disturbances like those produced when walking around humans. To achieve this capability, Mercury relies on an advanced inertial state estimation process and feedback control systems. The walking controller is based on whole-body control theory which enables precise trajectory tracking using the robot’s series elastic actuators. This means that the control methods of Mercury can be ported to many other humanoid robots with different morphologies and actuator setups. Finally, Mercury is a partial rebuild of the former Meka Hume biped, now including an Apptronik Medulla and Axon embedded nervous system. The legs have been partially redesigned and built to increase stiffness and incorporate the passive ankles. This research has been conducted at the Human Centered Robotics Lab at UT Austin.

[Airicist]

https://youtu.be/wnl0s2w2nmI

Mercury performs in the new lab

Published on Dec 19, 2018

[Airicist]

https://youtu.be/bZMvIYYmnc0

Mercury walks in rough terrain and in all directions

Published on Jan 24, 2019


Whole-body control (WBC) is a generic task-oriented control method for feedback control of loco-manipulation behaviors in humanoid robots. For this set of experiments, we devise a new WBC, dubbed whole-body locomotion controller (WBLC), that can achieve experimental dynamic walking on unsupported passive-ankle biped robots. A key aspect of WBLC is the relaxation of contact constraints such that the control commands produce reduced jerk when switching foot contacts. To achieve robust dynamic locomotion, we conduct an in-depth analysis of uncertainty for our dynamic walking algorithm called time-to-velocity-reversal (TVR) planner. The uncertainty study is fundamental as it allows us to improve the control algorithms and mechanical structure of our robot to fulfill the tolerated uncertainty. In addition, we conduct extensive experimentation for unsupported dynamic walking, unsupported directional walking, and unsupported walking over an irregular and slippery terrain.