Path finding and control in mobile autonomous robotic systems
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Path Finding And Control In Mobile Autonomous Robotic Systems Dan Hand COT 4810 February 19, 2002 Presentation Overview A robot is an computer-controlled electro-mechanical device Robotic systems can be grouped by movement capability: Constrained systems

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Path Finding And Control In Mobile Autonomous Robotic Systems

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Path finding and control in mobile autonomous robotic systems l.jpg

Path Finding And Control In Mobile Autonomous Robotic Systems

Dan Hand

COT 4810

February 19, 2002


Presentation overview l.jpg

Presentation Overview

  • A robot is an computer-controlled electro-mechanical device

  • Robotic systems can be grouped by movement capability:

    • Constrained systems

    • Free moving systems, we will call these mobile systems

  • Mobile robotic systems have some unique issues. This presentation will focus on two:

    • Path finding

    • Related control issues


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Path Finding

  • Applies to autonomous systems

  • Path Finding can consist of:

    • Trial and Error

    • Pre Planning + Adjustment (if needed)

  • Several approaches have been used to implement the intelligence in Path-Finding

    • Subsumption approach

    • Knowledge-based approach

  • Selection is dependent on information, sensors, and computer hardware available


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Path Finding Example

Consider the following situation:

Straight Path

Trial & Error Path

Target

Pre-Planned Path

Lake or Other Hazard

Robot


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Subsumption-Based Path-Finding

  • Corresponds roughly to a trial and error approach

  • Approach to “intelligence” in robotic systems

  • Proposed by R.A. Brooks in 1986

  • Advocates building agents by combining simple reflexive reactions

  • Characteristics

    • No explicit knowledge representation

    • Reflexive response to environment

    • Purely reactive

  • Behavior based systems extend subsumption architecture to add state storage


Subsumption architecture example l.jpg

Situational Behaviors – these will only be executed if the correct conditions exist

Avoid hazards

The default behavior usually takes no action but is the parent of all other behaviors in the system

Increasing Precedence

Move to target

Default behavior

Subsumption Architecture Example

  • Behaviors can be viewed as being placed in a stack

    • Behaviors with a lower precedence in the stack are said to be suppressed

    • Avoidance behavior has “highest” precedence here


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Subsumption Architecture Path Finding Example

Tree

Target

6

4

3

5

Initial Straight Line Course From Move To Target Behavior

Path With Obstacle Avoidance Behavior

Robot

2

1

Building

  • Active Behaviors At Each Point In The Diagram

  • ) Default, Move To Target

  • ) Default, Move To Target, Move Away From Hazards

  • ) Default, Move To Target

  • ) Default, Move To Target, Move Away From Hazards

  • ) Default, Move To Target

  • ) Default


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Knowledge-Based Path-Finding

  • Several knowledge-based mobile robots and techniques exist

  • Basic idea:

    • If information about the environment is well-known

      • Pre-planning a reasonable path based on known data

      • Adjustments can be made (if needed) along the way

    • If no or little information is available about the environment

      • Possible to collect information and store along the way

      • Problems arise with collecting accurate information

  • Disadvantage:

    • System highly reliant on accurate and detailed data on surroundings


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Control Overview

  • Control involves both sensing a condition and taking a action based on it

  • Control difficulty dependent on complexity of system hardware

    • Locomotion method

      • Wheels / Tracks

      • Legs

    • Number & type of sensors

    • Vision?

  • Operating environment issues

    • Sensing environment, converting into useful information

    • Localization


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Feedback From Output Device

Output

Device

Logic

Control System

Command

Output Based on Feedback

General Control Overview

  • Feedback from output devices is critical in mobile robotic systems to ensure operation in varying environments


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Feedback Example

  • Consider the example below

  • It is important to insure that each wheel spins at the correct rate for the vehicle to remain on course

Wheel

Sensor

Varying force applied to wheel

Top View

Motor Controller

Motor

Wheel Rotation


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Localization

  • Important control and sensing issue

    • Consists of precisely locating position on map

    • Needed to identify position relative to obstacles

  • Especially important to knowledge-based systems since error in positioning can accumulate

  • Numerous solutions exist

    • High-accuracy GPS

    • Landmark recognition

    • Odometers

    • Beacons


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Localization Continued

  • Sample situation with a standard GPS-Based system

Error in GPS Positioning

Distance to object

Object Detected By Sensors


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Sample Knowledge-Based Robot

TJ - Designed by Mark Torrance for his master’s thesis

Where are you?

I don't know where I am right now.

Which way are you facing?

I don't know which way I am facing. Please tell me.

You are facing north

I am facing NORTH. Thanks.

You are at Mark's office

I'm learning about MARK'S OFFICE.

Turn around

I'm turning around.

Go until you can turn right

I'm going until I see no obstacle on the right.

You are at the northeast entrance to the elevator lobby

I'm learning about THE NORTHEAST ENTRANCE TO THE ELEVATOR LOBBY.

Go

I'm going.

.

.

.

Designed to navigate around MIT offices

Uses an odometer for localization


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For Additional Information

  • Mobile Robots: http://www.ai.mit.edu/projects/mobile-robots/http://www.cc.gatech.edu/ai/robot-lab/

  • Subsumption Architecture: http://ai.eecs.umich.edu/cogarch0/subsump/http://www-formal.stanford.edu/eyal/lsa/

  • Motor Control / Feedback:http://e-www.motorola.com/webapp/sps/site/homepage.jsp?nodeId=03nQXG


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