Development of a swarming algorithm for mobile robots
Swarming robots basically consist of a group of several simple robots that interact and collaborate with each other to achieve shared goals. It is inspired by social insects, which can perform tasks that are beyond the capability of an individual. In a navigation task, a single robot system is not...
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Format: | Thesis |
Language: | English |
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Online Access: | http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/42989/1/P.1-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/42989/2/Full%20Text.pdf |
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Summary: | Swarming robots basically consist of a group of several simple robots that interact and
collaborate with each other to achieve shared goals. It is inspired by social insects, which can perform tasks that are beyond the capability of an individual. In a navigation task, a single robot system is not suitable to be used as an agent for the navigation usually covers a wide range of area. Furthermore, a single robot system is more complicated and requires
a higher cost to build since the mobile robots need to be more complex in order to enable
their abilities. Therefore, a group of simple robots is introduced. A group of robots can
perform their tasks together in a more efficient way compared to a single robot, hence
develop a more robust system. This thesis presents an approach for swarming algorithm
using autonomous mobile robots. This project implements the swarming algorithm by
supplementing the ability of mobile robot platforms with autonomy and odour detection.
The work focused on the localization of chemical odour source in the testing environment
and the leader and follower swarm formation through wireless communication. The
project was developed in stages, namely hardware implementation where the mobile
robots were given the ability to detect obstacles. A TGS 2600 Figaro sensor was utilized
to provide the ability to detect odour. To enable the mobile robots to communicate with
each other and able to perform leader and follower designation once the target has been
found, the robots were installed with X-Bee module. The robot which found the odour
source first will be the leader and the other will automatically become a follower. The
Received Signal Strength Indicator (RSSI) of X-Bee is used as the parameter to estimate
the distance between the leader and the follower robots. The algorithm was developed
using Arduino development environment. By combining these three algorithm stages, a
simple swarming system is tested. In this research, the leader-follower designation has
been proposed as the method of swarming searching behaviour. The results show that the
searching method provides a centralized communication between all the mobile robots.
This communication leads to a better wireless data exchange between mobile robots
compared to the distributed communication approach which decision making is based on
each agent in the testing environment. The RSSI used in this research shows the reliability
as an estimation parameter between mobile robots. The use of RSSI is a new method of
estimating the distance between two wireless communication nodes despite the widely
use of Bluetooth, ultrasonic sensors and Global Positioning System (GPS). Based on the
RSSI value, the swarming system experiment is demonstrated. From the results, future
work on the stabilization of the RSSI value during the wireless data transmission can be
further investigated. |
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