Target interception by mobile robots in a wireless sensor network

The main objective of this project is to implement an autonomous robot namely pursuer that can collaborate with sensor network to perform pursuing. The wireless sensor network will detect the intruders, then localize intruder and pass the localization information to the pursuer robot. The pursuer wi...

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Bibliographic Details
Main Author: Liu, Yan.
Other Authors: Xie Lihua
Format: Final Year Project
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/18009
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Institution: Nanyang Technological University
Language: English
Description
Summary:The main objective of this project is to implement an autonomous robot namely pursuer that can collaborate with sensor network to perform pursuing. The wireless sensor network will detect the intruders, then localize intruder and pass the localization information to the pursuer robot. The pursuer will communicate with the sensor node and compute an path to intercept the intruder with obstacle avoidance capability. This project involves both the hardware and software development for the autonomous robot. For the hardware part, several improvements and modifications have been made on the previous AmigoBot. Firstly, the stargazer has been added to the AmigoBot. It uses an intelligent vision system to do the localization with a relative high accuracy. It functions as a self-localizer of the AmigoBot. Secondly, the number of IR sensors and the orientation has been modified to maximize the obstacle avoidance capability. Previously, the robot came into collision with the static sensors a lot due to the dead region. Thirdly, a direct WiFi connection has been made which increases the stability of the connection. In addition, serial port has been expanded, and the battery has been replaced as well. For the software part, the Labview programming for both the navigation and the obstacle avoidance has been developed. The new navigation algorithm is based on adjusting the forward speed and rotational speed. The parameters are collected from the wireless sensor network and the stargazer. A real-time obstacle avoidance capability has been developed as well instead of potential field which has been done previously.