Control of humanoid robots
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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)

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Control of Humanoid Robots

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Control of humanoid robots

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

Assessment of Disruptive Technologies by 2025 (Global Trends)


Human centered robotics

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

Current Projects: Compliant Control of Humanoid Robots


Recent project guidance of gait using functional electrical stimulation

Recent Project:Guidance of Gait Using Functional Electrical Stimulation


Control of humanoid robots1

CONTROL OF HUMANOID ROBOTS


General control challenges

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

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

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

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

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

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

Model of Task Kinematics Under Multi-Contact Constraints

  • Operational point (task to joints)

qarms

  • Differential kinematics

xbase

x

  • Reduced contact-consistent Jacobian

qlegs


Control of humanoid robots

Modeling of Internal Forces and Moments


Variables representing the contact state

Variables representing the contact state


Aid using the virtual linkage model predict what robot can do

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

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

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


More details of the grasp contact matrix

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


Control of humanoid robots

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


Approach

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

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

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

Highly Redundant Systems Under Constraints


Prioritized whole body torque control

Prioritized Whole-Body Torque Control

  • Prioritization (Constraints first):

  • Gradient descent is in the manifold of the constraint


Constrained consistent gradient descent

Constrained-consistent gradient descent

x un-constrained

x task

  • Constrained kinematics:

  • Optimal gradient descent:


Constrained multi objective torque control

Constrained Multi-Objective Torque Control

  • Lightweight optimization

  • Decends optimally in constrained-consistent space

  • Resolves conflicts between competing tasks


Torque control of humanoids under contact

Torque control of humanoids under contact


Control of advanced skills

Control of Advanced Skills


Example interactive manipulation

Example: Interactive Manipulation


Control of humanoid robots

Control of internal forces

  • Manifold of closed loops

  • Unified motion / force / contact control


Compliant control of internal forces

Compliant Control of Internal Forces

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


Simulation results

Simulation results


Approach1

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

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

Automatic control of CoP’s and internal forces

Motion control


Com control

CoM control


Example com oscillations

Example: CoM Oscillations


Specifications

Specifications


Multiple steps forward trajectories

Multiple steps: forward trajectories


Results lateral steps

Results: lateral steps


Approach2

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

Demos Asimo

  • Upper body compliant behaviors

  • Honda’s balance controller

  • Torque to position transformer


Summary

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

PRESENTATION’S END


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