Cooperative Robotics Using Wireless Communication
Type of DegreeThesis
DepartmentElectrical and Computer Engineering
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Cooperative Robotics has to do with the use of multiple robotic agents assisting each other to perform a task that is either too difficult or impossible for one robot to perform alone. It is a multi-disciplinary field that spans the areas of computer science, electrical engineering, and artificial intelligence. Research scenarios often include tasks that are difficult, monotonous, or dangerous for humans to perform. This thesis presents a search-and-rescue algorithm, referred to as SARA-1, that is designed to enable a team of cooperative autonomous robots to search an area for a stationary target. The robots use wireless communication to build and share collective maps of the environment. They attempt to spread out their cooperative search, taking care not to explore the same area twice. This algorithm is pertinent to both indoor and outdoor applications. The range of applications is limited only by the user's imagination, and might include such tasks as hazardous waste location and removal, planetary exploration, warehouse organization, and human search-and-rescue. Several different experiments are performed using SARA-1 on the Player/Stage simulation platform, in two different simulated environments. Experiments involve varying the number of robots and the communication interval (how often the robots exchange data) to see how the time and success of a search-and-rescue task is affected. It is found, in the number of robots experiments, that there is a threshold at which the positive effects of cooperation are outweighed by inter-robot interference and communication overhead. Increasing the number of robots past this threshold has undesirable consequences including an increase in the time for task completion and a higher frequency of robot failure. In the communication experiments, it is found that a group of robots using any communication interval is superior to a group of robots that does not communicate. Choosing the communication interval that is most efficient is shown to be a much more complex task. More frequent communication provides more cooperation between robots, but requires more overall time for task completion. Less frequent communication slightly speeds up the time for task completion, but produces more interference among robots, increasing the risk of failure. The optimal selection of the number of robots and the communication interval depends highly on the specific task that is being performed.