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Fault Detection in Autonomous Assembly by Space Robot Using Semantic Task Model ISTS 2006 - s - 02 Keita Sawayama Dept. of Aeronautics & Astronautics, The University of Tokyo Contents Background Our Approach: Use of Semantic Information System Architecture Simulation Experiment

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fault detection in autonomous assembly by space robot using semantic task model

Fault Detection in Autonomous Assembly by Space Robot Using Semantic Task Model

ISTS 2006 - s - 02

Keita Sawayama

Dept. of Aeronautics & Astronautics, The University of Tokyo

contents
Contents
  • Background
  • Our Approach: Use of Semantic Information
  • System Architecture
  • Simulation Experiment
  • Conclusions
future space system
Future Space System
  • Sustainable Space System
    • Orbital Recycle & Reconfiguration
      • Assembly, Maintenance, Diagnosis

Autonomous Space Robots Applications

autonomous space robots
Autonomous Space Robots
  • Application to routine work
    • Ex. Small satellites orbital assembly

small satellite

  • Rule-based control
    • Conventional, Established control approach
rule based approach
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

IF

THEN

condition

command

Behavior

Rule

[move(x,y,z)]

rule based approach7
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

command 1

command 2

command 3

command 4

command 5

command 6

rule based approach8
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

command 1

command 2

command 3

command 4

command 5

command 6

rule based approach9
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

command 1

command 2

command 3

command 4

command 5

command 6

rule based approach10
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

command 1

command 2

command 3

command 4

command 5

command 6

rule based approach11
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

command 1

command 2

command 3

command 4

command 5

command 6

rule based approach12
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

command 1

command 2

command 3

command 4

command 5

command 6

rule based approach13
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

command 1

command 2

command 3

command 4

command 5

command 6

Misaligned!!

rule based approach14
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

command 1

command 2

command 3

command 4

command 5

command 6

rule based approach15
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

command 1

command 2

command 3

command 4

command 5

command 6

STOP!

Uncertainties in real world tasks

rule based approach16
Rule-based approach
  • Suitable for prescribed task sequences
    • Reliable execution

How to recover ?

command 1

command 2

command 3

command 4

command 5

command 6

STOP!

Uncertainties in real world tasks

problem of rule based approach
Problem of Rule-based approach
  • Not flexible to unexpected situations
    • Robots need more information for control

IF

THEN

condition

command

Behavior

Rule

[move(x,y,z)]

  • Semantics of the action
  • Purpose, Relevant objects,
  • Focused relations, ・・・

Semantic

Information

Key to Flexibility

our approach
Our Approach

~Use of Semantic Information~

our approach19
Our approach
  • Use of Semantic Information
    • Normal operations
    • Unexpected Situations

Rule-based control

Inference, Re-planning

Use of semantic information

semantic information behind command

Semantics of the behavior

Purpose :“Locate”

Object :“The blue block”

Target :“Beside the yellow block”

Semantic Information behind Command

Command

“move(0,0,-10)”

= Rule-basedBehaviordescription

+

・ Behavior understanding

・ Situation recognition

Basis forrational inference & planning

example of using s i
Example of Using S.I.

Command

“move(0,0,-10)”

+

Semantics of the behavior

Purpose : “Locate”

Object : “The blue block”

Target : “Beside the yellow block”

Behavior understanding

“Locate the blue block beside the yellow block”

Situation Recognition

“Under satellite assembly situation”

plan representation
Plan Representation

Robot Plan

Semantic Information (Annotation)

Commands

Similar to “Semantic Web” concept

control sequence
Control Sequence

Normal Mode

Command 1

Semantic

Information 1

Command 2

Semantic

Information 2

Command 3

Semantic

Information 3

control sequence25
Control Sequence

Normal Mode

Command 1

Semantic

Information 1

Command 2

Semantic

Information 2

Command 3

Semantic

Information 3

control sequence26
Control Sequence

Normal Mode

Command 1

Semantic

Information 1

Command 2

Semantic

Information 2

Command 3

Semantic

Information 3

control sequence27
Control Sequence

Normal Mode

Command 1

Semantic

Information 1

Command 2

Semantic

Information 2

Command 3

Semantic

Information 3

control sequence28
Control Sequence

Error occurs

Command 1

Semantic

Information 1

Command 2

Semantic

Information 2

Command 3

Semantic

Information 3

control sequence29
Control Sequence

Recovery Mode

Cause Inference

Sensing Planning

Command 1

Semantic

Information 1

Sensing Action

Command 2

Semantic

Information 2

Cause Verification

Command 3

Semantic

Information 3

Recovery Planning

Recovery Action

control sequence30
Control Sequence

Recovery Mode

Cause Inference

Sensing Planning

Command 1

Semantic

Information 1

Sensing Action

Command 2

Semantic

Information 2

Cause Verification

Command 3

Semantic

Information 3

Recovery Planning

Recovery Action

modeling method in stm33
Modeling Method in STM

Relation About

Adding Force

Force

Adding Force

Interferes

Reduction of

Moving Closer

Moving Closer

Obstacle Role

Force

By Obstacle

By Obstacle

Way N

Possible Causes

modeling method in stm34
Modeling Method in STM

Relation About

Adding Force

Force

Adding Force

Interfering

Reduction of

Moving Closer

Moving Closer

Obstacle Role

Use of Semantic Task Model

By Obstacle

By Obstacle

Way N

Way of Function Achievement

experiment scenarios

[Scenario 1]

[Scenario 2]

End Effector

Downward

Cell

Upward

Force

Force

Experiment Scenarios

Can the system recognize the different influence of the same force?

⇒ Influence ??

⇒ Influence ??

result

The WFAs of “Accelerating moving farther” are

---By pushed by something

---By inertial force

The WFAs of “Interfering moving closer” are

---By interfering moving path

---By failure in drive torque

---By mismatch in coordinate system

---By interrupting robot motion

Result

[Scenario 1]

[Scenario 2]

Same observation, Different interpretation

The system can output different causes.

Utilization of semantic information for fault detection and diagnosis

conclusion
Conclusion
  • New space robot control architecture
    • Rule-based + Semantic Information
    • The system utilizes semantic information for handling unexpected events.
  • Fault detection and diagnosis scheme
    • The system can understand the situation and infer the cause of the problem flexibly and rationally.

Application