Abstract

There are many things such as self-organizing behaviors that we human can learn from nature. Examples are like the flocking of birds and the foraging of ants. Such behaviors are commonly labelled as swarm Intelligence. Swarm intelligence is defined as a group of agents whom collective interaction magnifies the effects of individual agent behaviors, resulting in the manifestation of a swarm level behavior beyond the capability of a small subgroup of agents.

 

In recent years, there is an increasing research on developing swarms of Unmanned Aerial Vehicles (UAVs), or drones for surveillance and reconnaissance. This is because with multiple UAVs working together can complete a much more elaborate job. However, with complexity of multiple random behaviors in swarm intelligence, there is a need to study on collision avoidance as well as the path planning concepts to prevent catastrophic accidents.

1.             PROJECT DEFINITION

1.1.                Project Objective

The objective of this Capstone Project is to study the swarm concepts of collision avoidance and path planning swarm intelligence as part of the autonomous coordination for UAV systems.

 

The project aims to:

 

1. Analyze various collision avoidance and path planning concepts and algorithms.

 

2. Review on the algorithms with regard to the organization and coordination of multiplex UAV operations.

 

3. Study on the concept and limitations of simulation platform for swarm intelligence.

 

4. Implementing of the concepts into simulation.