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    Wireless mosaic eyes based robot path planning and control. Autonomous robot navigation using environment intelligence with distributed vision sensors.

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    Thesis (3.516Mb)
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    Publication date
    2010-08-27T15:55:04Z
    Author
    Cheng, Yongqiang
    Supervisor
    Hu, Yim Fun
    Jiang, Ping
    Keyword
    Distributed vision sensors
    Wireless sensor network
    Robot control
    Path planning
    Trajectory generation
    Accompanied snake
    Navigation
    Collaborative vision sensors
    Distributed artificial intelligences
    Rights
    Creative Commons License
    The University of Bradford theses are licenced under a Creative Commons Licence.
    Institution
    University of Bradford
    Department
    School of Engineering Design and Technology
    Awarded
    2010
    
    Metadata
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    Abstract
    As an attempt to steer away from developing an autonomous robot with complex centralised intelligence, this thesis proposes an intelligent environment infrastructure where intelligences are distributed in the environment through collaborative vision sensors mounted in a physical architecture, forming a wireless sensor network, to enable the navigation of unintelligent robots within that physical architecture. The aim is to avoid the bottleneck of centralised robot intelligence that hinders the application and exploitation of autonomous robot. A bio-mimetic snake algorithm is proposed to coordinate the distributed vision sensors for the generation of a collision free Reference-snake (R-snake) path during the path planning process. By following the R-snake path, a novel Accompanied snake (A-snake) method that complies with the robot's nonholonomic constraints for trajectory generation and motion control is introduced to generate real time robot motion commands to navigate the robot from its current position to the target position. A rolling window optimisation mechanism subject to control input saturation constraints is carried out for time-optimal control along the A-snake. A comprehensive simulation software and a practical distributed intelligent environment with vision sensors mounted on a building ceiling are developed. All the algorithms proposed in this thesis are first verified by the simulation and then implemented in the practical intelligent environment. A model car with less on-board intelligence is successfully controlled by the distributed vision sensors and demonstrated superior mobility.
    URI
    http://hdl.handle.net/10454/4421
    Type
    Thesis
    Qualification name
    PhD
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    Theses

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