HRTC Meeting 12 September 2002, Vienna Smart Sensors Thomas Losert.

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HRTC Meeting 12 September 2002, Vienna Smart Sensors Thomas Losert

Transcript of HRTC Meeting 12 September 2002, Vienna Smart Sensors Thomas Losert.

Page 1: HRTC Meeting 12 September 2002, Vienna Smart Sensors Thomas Losert.

HRTC Meeting12 September 2002, Vienna

Smart Sensors

Thomas Losert

Page 2: HRTC Meeting 12 September 2002, Vienna Smart Sensors Thomas Losert.

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Overview

• Smart Transducers(Definition, Observations, Interfaces)

• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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Overview

• Smart Transducers(Definition, Observations, Interfaces)

• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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Smart Transducer (ST)

Comprises the Integration of one or more Sensor/Actuator Elements with a Micro-controller and a Communication Network Interface that provides the following Services across standard Interfaces:

Diagnostic and Management Real-Time Communication Calibration of Sensor Signal Conditioning and Conversion to

standard Units

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Advantages

No noise pickup from long external signal transmission lines.

Better Diagnostics – Simple external ST failure modes (e.g., fail-silent)

"Plug-and-play" capability if the ST contains its own documentation on silicon or in an external database.

Reduction of the complexity at the system hardware and software and the internal ST failure modes can be hidden from the user by a well-designed fully specified ST interface.

Cost reduction in installation and maintenance.

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Overview

• Smart Transducers(Definition, Observations, Interfaces)

• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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Observations

An observation consists of an atomic tuple

< observed value, instant, RT-entity Name >

For Communication of Observations across an RS interface a common set of concepts is necessary:

Common representation of values in a Shared code-space Common notion of time and its representation Common meaning of the names of RT entities Access protocol to the information.

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Observations

An observation consists of an atomic tuple

< observed value, instant, RT-entity Name >

For Communication of Observations across an RS interface a common set of concepts is necessary:

Common representation of values in a Shared code-space Common notion of time and its representation Common meaning of the names of RT entities Access protocol to the information.

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State vs. Event Values

Characteristic State Observation

Event Observation

Value Full Value Value Difference

Frequency Periodic Sporadic

Loss of Observ. Period lost Loss of synch.

Semantics At-least-once Exactly-once

Error Detection At receiver At sender only

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Observations

An observation consists of an atomic tuple

< observed value, instant, RT-entity Name >

For Communication of Observations across an RS interface a common set of concepts is necessary:

Common representation of values in a Shared code-space Common notion of time and its representation Common meaning of the names of RT entities Access protocol to the information.

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GPS - Time

GPS weeks and GPS seconds since the GPS epoch

(6. Jan. 1980, 00:00:00 UTC)

Advantages:

• Continuous representation of Time(no leapseconds)

• High availability with low jitter

Disadvantages:

• Overflow every 19.6 years because GPS week is represented as a 10 bit value

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Based on GPS; advantages of GPS are preserved

Additional advantages:• Enhanced granularity (about 60 ns)• Easy Access to the full second• No overflow during the lifetime of the product

(horizon of more than 10 000 years)• Easy manipulation of timestamps

Global Notion of Time

2-24 seconds

external time format (8 bytes)

1 sec (20 seconds)239 seconds

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Observations

An observation consists of an atomic tuple

< observed value, instant, RT-entity Name >

For Communication of Observations across an RS interface a common set of concepts is necessary:

Common representation of values in a Shared code-space Common notion of time and its representation Common meaning of the names of RT entities Access protocol to the information.

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Interface File System (IFS)

Hierarchical, distributed File-System that is the

Source and Sink of each communication

Map all relevant properties of a node into the IFS:

• Sensor and actuator data

• Calibration data, parameters, etc.

• Configuration Information

• Node identification (physical name, global name)

• Documentation and pointer to register service

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Global Name

Transducer Node

CORBA-Gateway

Active Master

Active Master

Active Master

Cluster A Cluster B Cluster C

Is the concatenation of

Cluster Name,

Logical Name

File Name, and

Record Name

• Up to 250 Clusters

• Up to 250 Nodes

• Up to 64 Files

• Up to 256 Records

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Observations

An observation consists of an atomic tuple

< observed value, instant, RT-entity Name >

For Communication of Observations across an RS interface a common set of concepts is necessary:

Common representation of values in a Shared code-space Common notion of time and its representation Common meaning of the names of RT entities Access protocol to the information (see TTP/A).

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Overview

• Smart Transducers(Definition, Observations, Interfaces)

• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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Three Interfaces of a Node

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Overview

• Smart Transducers(Definition, Observations, Interfaces)

• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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Why Time-Triggered?

• Requirement to record value and instant when measurement was performed

• Requirement to perform synchronous distributed measurements

• Requirement to gather multiple measurements with bounded delay

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Principles of Operation: Temporal Firewall

• Best way of communication for Producer• Best way of communication for Consumer• Predictable time-triggered communication• Components have access to a global time• Communication and measurement synchronized• Temporal firewall in communication

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Time-Triggered Protocol/Class A (TTP/A)

• Low-cost time-triggered sensor bus• Supports „Smart Transducers“• Currently subject of a standardization

process at Object Management Group

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Principles of Operation: TTP/A (1)

• One active master• Up to 250 slaves• Communication organized in rounds• TDMA bus allocation

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Principles of Operation: TTP/A (2)

• Time-Triggered Protocol for Fieldbus Applications

• TDMA Bus Access Scheme

• Communication Organized into Rounds

• Supports Various Physical Layers

Each round is initiated by the master by sending the

Fireworks-Byte

• Multipartner (MP): Real-Time Service Interface

• Master/Slave (MS): Monitoring and Configuration

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TTP/A: Principles of Operation (2)

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Overview

• Smart Transducers(Definition, Observations, Interfaces)

• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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Architecture

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CORBA

CORBA Smart Transducers Interface (STI)• Allows (re)configuration of the Smart

Transducer cluster, e.g. over the internet• Allows monitoring of the ST cluster• Allows access to the real-time service

interface for cases, when a RT-CORBA supporting end-to-end predictability is used

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Overview

• Smart Transducers(Definition, Observations, Interfaces)

• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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„Sensor Fusion is the combination of sensory data or data derived from sensory data such that the resulting information is in some sense better than would be possible when these sources were used individually.“

Definition of Sensor Fusion

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„better“ can mean:• More robust (fault-tolerant sensor clusters)

• Extended spatial and temporal coverage

• Increased confidence

• Reduced ambiguity and uncertainty

• Robustness against interference

• Improved resolution

• Emerging services

Purposes of Sensor Fusion

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Overview

• Smart Transducers(Definition, Observations, Interfaces)

• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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A Typical Sensor Fusion Control Loop

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Introducing a Sensor Fusion Model

Three levels of computation:• Node level• Cluster level• Control application level

Well-defined interfaces between levels• Smart Transducer Interface• Environmental image

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Control Loop in the Three-Level Model

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Overview• Smart Transducers

(Definition, Observations, Interfaces)• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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Case Study:Autonomous Mobile Robot

• TTP/A fieldbus network with 1 master• 1 node for sensor fusion and navigation• 15 smart transducers (9 actuators/6 sensors)

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ST-Types

• 2 Ultrasonic Far Distance Sensors• 3 Infrared Low Distance Sensors• 1 Luminance Sensor

• 1 Steering Control• 1 Speed Control• 3 Servos for Moving Infrared Sensors• 4 Lighting Control

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Control Loop

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The „Smart Car“

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Overview

• Smart Transducers(Definition, Observations, Interfaces)

• Principles of Operation• Architecture• Sensor Fusion (Definition, Concepts)• Case Study• Conclusion & Outlook

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Conclusion & Outlook

Case Study• Proof of concept for TTP/A• Testbed for Sensor Fusion• Demonstrator for CORBA-STI

The Standard Proposal has been adopted in Jan. 2002 by the Board of Directors and is called Smart Transducers Interface Standard now. The standardization process continues ...

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Thank you for your attention!