Multiple Autonomous Ground/Air Robot Coordination Exploration of AI techniques for implementing incremental learning. Development of a robot controller for navigation of mobile robot in a maze like environment. Testing the effectiveness of the robot controller in simulated and real environments. Experimentation: Theory: Swarm behavior introduces intelligent capabilities such as adaptation and self-organization to a multi-robot system. Essential for generating creativity and innovation in emergent structures.

Development of Integrated Multi-Aerial and Ground vehicle Experimental Platform Proposed Equipment: Skybotix Coax miniature helicopter (x8) Quanser Q-Ball (x1) Insight 5600 Vision Sensor (x6) Dell Workstation w/Xeon Quad Core Processor (x1) Softwall Enclosure for Platform Research and Educational Applications of the Platform: Distributed cooperative control in complex systems, swarm robotics, and network science Decision making in uncertain and complex environment Distributed sensing and sensor fusion Supervisory control of multiple UAVs Activities: Assist in procurement of UAV helicopters Installation of required lab tools and testing environment Integration of hardware with various software interfaces

Preliminary Experimentation Multi-Robot UAV Testbed: Existing and new platform will be used to carry out experimentations Experiments include formation control and collective data gathering Algorithms are tested in simulation Code transferred via TCP/IP architecture Player server enables use of sonar, infrared, motor, and power devices via Wi-Fi Overhead Cogex Cameras and motion capture system provide global positioning information to individual units Dedicated wireless modem allows for concurrent communication between server and robotic swarm