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Robotics science fair project:
A robot that can tell where objects are (map-building)




Science Fair Project Information
Title: A robot that can tell where objects are (map-building)
Subject: Robotics / Electronics
Grade level: High School - Grades 10-12
Academic Level: Advanced
Project Type: Experimental
Cost: High
Awards: 1st place, Canada Wide Virtual Science Fair (2004)
Affiliation: Canada Wide Virtual Science Fair (VSF)
Year: 2004
Description: The purpose of this project was to discover if a robot could navigate using a system based on parallax to optically analyze its environment.
Link: http://www.virtualsciencefair.org/2004/kram4r0/public%5Fhtml/
Short Background

Robot navigation means its ability to determine its own position in its frame of reference and then to plan a path towards some goal location. In order to navigate in its environment, the robot or any another mobility device requires representation i.e. a map of the environment and the ability to interpret that representation.then we talk about robot itis very useful for college and school students. Navigation can be defined as the combination of the Three fundamental competences:

  • Self-Localisation
  • Path Planning
  • Map-Building and Map-Interpretation

Map in this context denotes any one-to-one mapping of the world onto an internal representation. In robots, this representation takes the form of artificial neural network excitation patterns.

Localisation denotes the robot's ability to establish its own position and orientation within the frame of reference. Path planning is effectively an extension of localisation, in that it requires the determination of the robot's current position and a position of a goal location, both within the same frame of reference or coordinates. Map building can be in the shape of a metric map or any notation describing locations in the robot frame of reference.

Vision-Based Navigation uses optical sensors include laser-based range finder and photometric cameras using CCD arrays to extract the visual features required to the localisation in the surrounding environment. However, there are a range of techniques for navigation and localisation using vision information, the main components of each technique are:

  • representations of the environment.
  • sensing models.
  • localisation algorithms.

In order to give an overview of vision-based navigation and its techniques, we classify these techniques under indoor navigation and outdoor navigation.

The easiest way of making a robot go to a goal location is simply to guide it to this location. This guidance can be done in different ways: burying an iductive loop or magnets in the floor, painting lines on the floor, or by placing beacons, markers, barcodes etc. in the environment. Such Automated Guided Vehicles (AGVs) are used in industrial scenarios for transportation tasks.

Source: Wikipedia (All text is available under the terms of the GNU Free Documentation License)

For More Information: Vision-Based Positioning

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