1. 788.11J Presentation “Flock Control: Using Information Energy” Presented by Mukundan Sridharan

2. The Main Idea Use a Flock of Bat-sized Micro Aerial Vehicles (MAV) to sense the air of a medium sized city (20 km radius and 2 Km height), for toxic material. The MAVs form a Ad hoc network and relays the data back to a ground control centre. We want more sensing nodes in areas of higher toxic plumes As the MAVs move the communication with the base station should not be interrupted.

3. The Main Achievements Information Energy gradient for command and control: –How important is a certain region –Based on: Quality of data sensed by the node and its neighbors Amount of data relayed to BS by the node and its neighbors –More important a region, less is the repelling potential for the nodes in the region

4. The Challenges 1.Avoiding Collision between MAVs 2.Dispersing MAVs to search for contaminated areas 3.Bounding vehicle movement to a limited coverage volume (preventing MAVs from hitting buildings) –Based on the first three conditions each node calculates a repelling potential –This achieves uniform distribution in the coverage volume, in the absence of any toxic plumes 4.Encouraging some MAVs to cluster in the vicinity of toxic plumes –As the quality of data sensed increases, the repelling potential of the node is decreased, attracting other nodes to the area. 5.Maintaining network connectivity between the MAVs in plumes to the ground control centre –A weighted average of unit vectors pointing from BS to each MAV, is computed –Vectors are weighted based on the data quality of the nodes –The weighted average vector points in the direction of the plume from BS –MAVs closer to this vector decrease their repelling potential

5. Picture of MAV under development at University of Colorado

6. Results Only Simulation Results A 147 node flock is simulated, which form a ad hoc network, to cover a volume of 40 X 40 X 1(km) The communication range of nodes, assumed to be >5km (?)

7. Simulation of flock behavior for rules 1,2 and 3

8. MAV motions using information energy with data clustering effects

10. MAV motions using information energy with both data and communication clustering effects

11. References 1.Information Energy for Sensor-Reactive UAV Flock ControlInformation Energy for Sensor-Reactive UAV Flock Control

12. Comments and Questions