Here you will find an explanation of ROS. The open source ROS has been chosen as the software platform to enable the network structure, relying on a publisher-subscriber model to allow for inter-robot communication and coordination.
This section explores our use of hardware and computer vision algorithms in relation to localization. The role of the localization subsystem is to provide state estimates of agents to the larger system.
The MURO lab utilizes turtleBots created at Willow Garage. Turtelbots are the ground robots in our testbed. They are useful for verifying control algorithms performance on hardware.
This section explores our interest in drones. These drones or quadrotors differ from the turtleBots in that they provide relaxed dyanmic constraints, which leads to a more flexible testbed for implementing various multi-agent robotic algorithms.
Here you will find an expalnation of Simultaneous Localization and Mapping, which is otherwise known as SLAM. In short SLAM consists of a robot building of a map of its surroundings using an estimate of its location while simultaneously estimating its location using the map of its surroundings.
The MURO lab utilizes an android tablet application as a tool for human-swarm interactions. Our android application uses ROS in order to communicate each of the active robots in the multi-agent network. This section explains the different applications where the app is useful.
ORB-SLAM allows us to do what is sometimes difficult in the world of robotics - onboard localization. Read this section to find out more.