Development Of A Swarming Algorithm For Mobile Robots
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Development of a Swarming Algorithm for Mobile Robots
Swarming robots basically consist of a group of several simple robots that interactand 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 developa 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.
Algorithmic Foundations of Robotics V
This book includes selected contributions to the Workshop WAFR 2002 being held at December 15-17, 2002 in Nice, France. This fifth biannual Workshop on Algorithmic Foundations of Robotics focuses on algorithmic issues related to robotics and automation. The design and analysis of robot algorithms raises fundamental questions in computer science, computational geometry, mechanical modeling, operations research, control theory, and associated fields. The highly selective program highlights significant new results such as algorithmic models and complexity bounds. The validation of algorithms, design concepts, or techniques is the common thread running through this focused collection.
Handbook of Research on Fireworks Algorithms and Swarm Intelligence
In recent years, swarm intelligence has become a popular computational approach among researchers working on optimization problems throughout the globe. Several algorithms inside swarm intelligence have been implemented due to their application to real-world issues and other advantages. A specific procedure, Fireworks Algorithm, is an emerging method that studies the explosion process of fireworks within local areas. Applications of this developing program are undiscovered, and research is necessary for scientists to fully understand the workings of this innovative system. The Handbook of Research on Fireworks Algorithms and Swarm Intelligence is a pivotal reference source that provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm. This book is ideally designed for researchers, data scientists, mathematicians, engineers, software developers, postgraduates, and academicians seeking coverage on this evolutionary computation method.