Thank you for visiting the website of the Robotics Swarm Research Group at Valparaiso University! We invite you to learn more about the research activity that our group is engaged in. Feel free to check the descriptions and videos of the various projects. If you are interested in more technical details, you can download the pdf posters and papers in the “Publications and Presentations” section. Finally, you can visit our “The Team” section to meet our team members. Please do not hesitate to contact us if you have any additional questions or suggestions.
The Ant Colony Optimization (ACO) algorithm is an evolutionary algorithm that bio-mimics the behavior of ants in finding the shortest path between an origin and a destination within a set of pre-determined constraints.
Autonomous Local Identification
With the emergence of swarm intelligence, system designers are creating robotic swarms of continuously increasing sizes. As the size of a swarm increases, it is imperative to have a uniform program collectively downloaded on all the agents in it.
In preparation for the robotic football competition this year, one of our research teams decided to create a robotic dance team to complement the football playing robots.
The goal of this project is to implement the Particle Swarm Optimization (PSO) method to determine a “maximum” interest point in a search space.
In this project, the goal is to use the spanning tree algorithm to help the kilobots to communicate relevant information to each other and to converge at a point of interest.
