Control of humanoid robots
This presentation is the property of its rightful owner.
Sponsored Links
1 / 50

Control of Humanoid Robots PowerPoint PPT Presentation


  • 113 Views
  • Uploaded on
  • Presentation posted in: General

Control of Humanoid Robots. Personal robotics. Guidance of gait. 12 November 2009, UT Austin, CS Department. Luis Sentis, Ph.D. Assessment of Disruptive Technologies by 2025 (Global Trends). Human-Centered Robotics. Human on the loop: Personal / Assitive robotics (health)

Download Presentation

Control of Humanoid Robots

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Control of Humanoid Robots

Personal robotics

Guidance of gait

12 November 2009,

UT Austin, CS Department

Luis Sentis, Ph.D.


Assessment of Disruptive Technologies by 2025 (Global Trends)


Human-Centered Robotics

  • Human on the loop:

  • Personal / Assitive robotics (health)

  • Unmanned surveillance systems (defense / IT)

  • Modeling and guidance of human movement (health)


Current Projects: Compliant Control of Humanoid Robots


Recent Project:Guidance of Gait Using Functional Electrical Stimulation


CONTROL OF HUMANOID ROBOTS


General Control Challenges

  • Dexterity: How can we create and execute advanced skills that coordinate motion, force, and compliant multi-contact behaviors

  • Interaction: How can we model and respond to the constrained physical interactions associated with human environments?

  • Autonomy:How can we create action primitives that encapsulate advance skills and interface them with high level planners

PARKOUR


The Problem (Interactions)

Coordination of complex skills using compliant multi-contact interactions

  • Operate efficiently under arbitrary multi-contact constraints

  • Respond compliantly to dynamic changes of the environment

  • Plan multi-contact maneuvers


Key Challenges (Interactions)

  • Find representations of the robot internal contact state

  • Express contact dependencies with respect to frictional properties of contact surfaces

  • Develop controllers that can generate compliant whole-body skills

  • Plan feasible multi-contact behaviors


Approach (8 years of development)

  • Models of multi-contact and CoM interactions

  • Methodology for whole-body compliant control

  • Planners of optimal maneuvers under friction

  • Embedded control architecture


Humanoids as Underactuated Systems in Contact

  • Model-based approach: Euler-Lagrange

Non-holonomic Constraints(Underactuated DOFs)

External Forces

Torque commands

Whole-bodyAccelerations

External forces


Model of multi-contact constraints

Assigning stiff model:

  • Accelerations are spanned by the contact null-space multiplied by the underactuated model:


Model of Task Kinematics Under Multi-Contact Constraints

  • Operational point (task to joints)

qarms

  • Differential kinematics

xbase

x

  • Reduced contact-consistent Jacobian

qlegs


Modeling of Internal Forces and Moments


Variables representing the contact state


Aid using the virtual linkage model (predict what robot can do)

C

C

C

C

Internal tensions

Center of Mass

Center of pressure points

Grasp / Contact Matrix

Normal moments


Properties Grasp/Contact Matrix

  • Models simultaneously the internal contact state and Center of Mass inter-dependencies

  • Provides a medium to analyze feasible Center of Mass behavior

  • Emerges as an operator to plan dynamic maneuvers in 3d surfaces


Example on human motion analysis(is the runner doing his best?)


More Details of the Grasp / Contact Matrix

  • Balance of forces and moments:

  • Underdetermined relationship between reaction forces and CoM behavior:

Optimal solution wrt friction forces


Example on analysis of stability regions (planning locomotion / climbing)


Approach

  • Models of multi-contact and CoM interactions

  • Methodology for whole-body compliant control

  • Planners of optimal maneuvers under friction

  • Embedded control architecture


Torque control: unified force and motion control(compliant control)

Control of the task forces (pple virtual work)

Control of the task motion

Stanford robotics / AI lab

Linear Control

Potential Fields


Inverse kinematics vs. torque control

Torque control:

Inverse kinematics:

duality

Pros:

Forces appear

Compliant because of dynamics

Cons:

Requires torque control

Pros:

Trajectory based

Cons:

Ignores dynamics

Forces don’t appear


Highly Redundant Systems Under Constraints


Prioritized Whole-Body Torque Control

  • Prioritization (Constraints first):

  • Gradient descent is in the manifold of the constraint


Constrained-consistent gradient descent

x un-constrained

x task

  • Constrained kinematics:

  • Optimal gradient descent:


Constrained Multi-Objective Torque Control

  • Lightweight optimization

  • Decends optimally in constrained-consistent space

  • Resolves conflicts between competing tasks


Torque control of humanoids under contact


Control of Advanced Skills


Example: Interactive Manipulation


Control of internal forces

  • Manifold of closed loops

  • Unified motion / force / contact control


Compliant Control of Internal Forces

  • Using previous torque control structure, estimation of contact forces, and the virtual linkage model:


Simulation results


Approach

  • Models of multi-contact and CoM interactions

  • Methodology for whole-body compliant control

  • Planners of optimal maneuvers under friction

  • Embedded control architecture


Contact Requisites: Avoid Rotations and Friction Slides

Rotational Contact Constraints:

Need to maintain CoP in support area

C

Frictional Contact Constraints:

Need to control tensions and CoM behavior to remain in friction cones


Automatic control of CoP’s and internal forces

Motion control


CoM control


Example: CoM Oscillations


Specifications


Multiple steps: forward trajectories


Results: lateral steps


Approach

  • Models of multi-contact and CoM interactions

  • Methodology for whole-body compliant control

  • Planners of optimal maneuvers under friction

  • Embedded control architecture


Demos Asimo

  • Upper body compliant behaviors

  • Honda’s balance controller

  • Torque to position transformer


Summary

  • Models of multi-contact and CoM interactions

  • Methodology for whole-body compliant control

  • Planners of optimal maneuvers under friction

  • Embedded control architecture

Grasp Matrix


PRESENTATION’S END


  • Login