Transcript Darainy

Evaluation and Modeling of Learning Effects on
Control of Skilled Movements through Impedance
Regulation and Model Predictive Control
By: Mohammad Darainy
Supervisor: Dr. Towhidkhah
Advisors: Dr. Rostami, Dr. Ostry
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Contents
 Introduction
 Control of Human Arm Impedance in Statics
 Transfer and Durability of Acquired Patterns of
Human Arm Stiffness
 The Role of Phasic Muscle Activity on Hand
Stiffness during Reaching Movements
 Modeling of Human Motor Control System through
Impedance control and Model Predictive Control
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What is The Joint Impedance?
 The Automatic Capability of the System to Resist an
Applied Load before Voluntary Intervention Takes Place
(Winters et al. 1988)
 Stiffness is defined as the ratio of change in force or
torque to change in length or angle
 Viscosity is defined as the ratio of change in force or
torque to change in velocity or angular velocity
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Which Parameters Contribute to the Joint
Impedance?
 Musculoskeletal Geometry has a Great Impact on
Joint Impedance
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Roughly Speaking, The Axis of
Maximum stiffness is a Line
that Connect The Hand to a
Point between Shoulder and
Half Way Through the Elbow
Mussa-Ivaldi et al. 1985
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Which Parameters Contribute to the Joint
Impedance?
 Musculoskeletal Geometry has a Great Impact on
Joint Impedance
 Level of Muscle Co-Contraction
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Adapted From Gomi & Osu 1998
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Which Parameters Contribute to the Joint
Impedance?
 Musculoskeletal Geometry has a Great Impact on
Joint Impedance
 Level of Muscle Co-Contraction
 Reciprocal Activation of Agonist – Antagonist Muscles
(Hunter & Kearney et al. 1982)
 Stretch Reflex Gain (Bennett 1994)
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What is Impedance Control?
 The Idea that the Nervous System Can Modify the
Mechanical Behavior of the Neuromuscular Periphery,
Known as Impedance Control Theory (Hogan 1985)
 Empirical Evidence:
 It was Shown That Subject Increase the Level
of Co-Contraction in Proportion to The Level of
Destabilizing Load (Milner & Cloutier 1998)
 During Two-Joints Movement, It was Shown
That The Subject Learn To Stabilize Unstable
Dynamics Using Selective Control of Impedance
Geometry. (Burdet et al. 2001)
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Co-Contraction Increase
The Mechanical Stability of
The Joint But at Greater
Metabolic Cost
Burdet et al. 2001
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The Focus of This Thesis
The Effect of Learning on Joint Stiffness.
The Coordinate System under which Impedance
Control will be Learned and Generalized.
The Impedance Control Limitation, Both in Statics
and Dynamics.
To Develop a Model of Human Motor System Based
on the Empirical Studies on Joint Impedance.
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1: Learning to Control Arm Stiffness under
Static Conditions
Aim
To Examine The Idea That Impedance Control
Involves a Process of Learning That is Acquired
Over Time and Permits the Voluntary Control of
The Pattern of Stiffness at The Hand.
 Prediction
We Predicted That The Subjects Can Voluntarily
Control Their Hand Impedance Geometry and
With Practice They Can Improve Their Ability of
Impedance Control
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Experimental Setup
Arm Configuration During The
Experiment
Interactive Motion Technologies,
Cambridge MA
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Experimental Study
 Subjects trained for three successive days
to resist one of three loads
 single axis loads in lateral direction.
 single axis loads in forward/backward direction.
 isotropic loads in eight directions about a circle.
 Unpredictable
servo-position
controlled
perturbations used to assess stiffness.
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Position Servo Controls Were
Used to Estimate The Stiffness
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Results
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Results
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Modeling Results
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Conclusion 1
 Stiffness Ellipse Modified With Learning in an Adaptive
Fashion, Change in Orientation Matches The Direction of
Load.
 Modeling Studies Suggest Separate Commands for
Shoulder and Elbow Co-Contraction.
 Even with Practice, Impedance Change in Statics is
Relatively Small in Magnitude. Simulations Suggest This is
at a Limit Regardless of Level of Co-Contraction.
 Clockwise Rotation of Stiffness Ellipse Greater Than AntiClockwise Rotation. Same Asymmetry in Simulations.
Asymmetry Due to Geometry Since Simulated Commands
Equate for Impedance of Shoulder and Elbow Muscles.
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2: Transfer and Durability of Acquired
Patterns of Human Arm Stiffness
Aims
 To Explore Whether Subjects Could Transfer
Stiffness Learning to Other Parts of The Workspace
And Also The Specific Pattern of Generalization as
a Means to Identify The Coordinate System in
Which The Learning Occurs.
 To Evaluated The Durability of Stiffness Training.
Is The Effect of Learning Persist Well beyond The
Time of Initial Learning?
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Experimental Setup
Arm Configuration During The Experiment 1 and 2
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Experimental Study
 The Tests Conducted With The Arm Stationary.
 In Experiment 1 Subjects Were Trained at The
Left And Transfer Test Was Conducted at The
Right. The Experiment Take Place in One Day.
 After The Training Phase Subjects Were Randomly
Assigned to One of Two Groups.
 One Group of Subjects Experienced Similar Torque at The
Left And Right (Group J) While for The Other Group The
Experienced Force at The Hand Was Similar (Group H).
 In Experiment 2 Subjects Were Tested for Three
Consecutive Days at The Left. The Direction of The
Force Application at The Third Day Was
Perpendicular to The Last Two days.
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Results Experiment 1
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Results Experiment 1
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Result Experiment 2
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Conclusion 2
 Experiment
1:
 Both Groups of Subjects in The Training Phase of The
Experiment Learned Successfully to Modify The Orientation of
The stiffness Ellipse.
 Transfer of Stiffness Control Was Observed only When The
Direction of Load Resulted in Torques That Were Similar to Those
Experienced During Training.
 Experiment 2:
 Subjects in The First Two Days of Experiment Learned to Modify
The Orientation of The stiffness Ellipse. The Change in Stiffness
Ellipse Orientation Matched The Direction of Force Application
 Higher Stiffness Ellipse Size, Longer Time Outside The Target
as Well as The Orientation of The Stiffness Ellipse on The Third
Days of Experiment Shows That The Stiffness Learning Result in
Durable Changes in Neural Signals Underpinning Co-Contraction
of Muscles.
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3: The Role of Phasic Muscle Activity on
Hand Stiffness during Reaching Movements
Aims
 To Develop a New Method for Stiffness Estimation
During Reaching Movements.
 To Explore The Effect of Phasic Muscle Activity On
Hand Stiffness During Reaching Movements By
Comparing The Static Stiffness with The Stiffness
During Movements.
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Experimental Setup
Arm Configuration During The Experiment
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Experimental Study
 The Tests Were Conducted in Three Consecutive
days
 The Stiffness Ellipses Were Estimated in Three
Different Conditions: Static, Down to Up and Left to
Right Reaching Movements.
 The Average of Last Eighty Trials During
Reaching Movements and AR Model of Trial By
Trial Variability Were Used as a Method for
Prediction of Ongoing Movements.
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Material and Method
The Result of Position Servo Control in Both X and Y
Direction For Reaching Movement in Y Direction.
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Results
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Results
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Conclusion 3
 The Result Shows Considerable Counter Clockwise
Rotation of Stiffness Ellipse in Compare to The Static
Stiffness Ellipse During Down to Up Reaching Movements.
 The Rotation of Stiffness Ellipse During
Reaching Movement Wasn’t Statistically Reliable.
Lateral
 Impedance Modification During Reaching Movements in
Unstable Environments May Actually Have Limitations
That Are Comparable to Those Observed Under Static
Conditions. The Large Empirical Difference May be Due
Simply to Phasic Muscle Activity During Movement.
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4: A Model of Motor Control System Based
on Impedance and Model Predictive Control
Aims
 To Develop a New Model for Motor Control System
Based on The Result of Empirical Impedance
Measurements During Acquisition of a New Skill.
 Try to Model The Effect of Learning on The Joints
Impedance.
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Model Structure
A Combination of Model Based Controller (MPC)
and Impedance Controller as a Model of Motor
Control System
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Simulations Conditions
Reaching Movements of 15cm Toward Each of Eight
Equidistance Targets Were Simulated
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Robot Model
The Model of Robot Defined
as: Fext  bX  k ( X  X * )
In First Step 0 Assigned to K
and b=[0 8; -8 0]N/m. This
is The Model of a Curl Field.
The Model Behavior Evaluated in Curl Field
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Simulation Results
To Control our Arm Perfectly
We Not Only Need The Model
of Environmental Dynamics
But Also We Need to Know
The Optimal Impedance of
The Joints in Each Situation.
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Simulation Results
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Simulation Results
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Simulation Results
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Simulation Results
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Simulation Results
The Model of Robot Defined
as: Fext  bX  k ( X  X * )
In This Case 0 Assigned to b
and k=[150 0; 0 0]N/m. This is
The Model of a Divergent
Force Field.
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Simulation Results
The Controller Doesn’t Benefit
too much from Having The
Model of Disturbance.
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Conclusion 4
 To do a Skilled Movement, We Need a Precise Model of
Environmental Dynamics Also The Optimal Impedance of
Participating Joints are Necessary as well.
 The Empirical Evidence Shows that The Subject’s
Performance Decay With The Distance from The Location
Where The Adaptation Take place. Our Simulation Argue
That The Unavailability of Optimal Impedance in
Neighboring Location is The Reason for The Above
Phenomena.
Adaptation to The Stable And Unstable Dynamics Have
Some Fundamental Deference. While The Adaptation to
Stable Dynamics Seems to Happen Mostly in Model Based
Controller, Adaptation to The Unstable Dynamics Achieved
By Impedance Control.
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General Conclusions
 Joint Impedance Can be Modified With Learning in an
Adaptive Fashion. Geometrical Changes in Impedance
Matches The Direction of Load.
 Impedance Control Learned and Generalized in Intrinsic
Coordinate System.
 Learning Impedance Results in Durable Changes to The
Neural Signals That Underlie Impedance Control.
 Impedance Control in Dynamics Have The same
Limitation That Were Seen in Statics.
 A Combination of Model Based Controller With
Impedance Controller Can Mimic The Behavior of Human
Subjects in Adaptation to Stable and Unstable Dynamics.
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Contribution to Knowledge
 For The First Time, The Effect of Learning on
Geometrical Pattern of Hand Stiffness Was evaluated in
This Thesis.
 The Coordinate System Under Which The Impedance
Control Learned and Generalized, Were Explored. These
Finding Help us to Understand How Subjects Percept The
Environmental Dynamics.
 The Empirical Studies Showed That Although The
Stiffness Control Under Static Conditions is Limited But
Stiffness Learning is Durable and The Effect of Learning
Can be Seen Well Beyond The Time of Initial Learning.
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Contribution to Knowledge
 A New Method of Stiffness Estimation During Reaching
Movements Developed and Applied.
 For The First Time, Both Static and Dynamic Stiffness at
The Same Musculoskeletal Geometry were Estimate. The
Results Argue That Stiffness Control During Movements
May Have The Same Limitation as it Was Shown Under
Static Conditions.
 A New Model for Motor Control System Were Presented
Based on Combination of a Model Based Controller and
Impedance Controller.
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