# 22: Optimal Unmanned Swarm Motion in the Presence of Faulty Nodes
Project ID:
22
Team Members:
Atul Shrotriya, Saina Namazifard
Faculty Advisor(s):
Frank Lewis
Department:
Electrical Engineering
Project Type:
Graduate
Title:
Optimal Unmanned Swarm Motion in the Presence of Faulty Nodes
Abstract:
Controlling robots in swarm motion to achieve set tasks is a highly interesting field garnering a significant amount of research focus. Such robot formations can be of exceptional use during rescue missions where time is a crucial factor and/or human intervention is not possible. During strenuous working conditions, it is possible for a robot to malfunction. This project implements two basic approaches to control robot swarms and then isolate a faulty robot using the method of trust consensus. It also generates an optimal path for best cost efficiency in terms of time or energy efficiency and dynamically calculates trust values based on individual node behavior.