1. “Microbotics”

2. Introduction INSPIRED by the biology of a bee and the insect’s hive behavior... we aim to push advances in miniature robotics and the design of compact high-energy power sources; spur innovations in ultra-low-power computing and electronic “smart” sensors; and refine coordination algorithms to manage multiple, independent machines.

3. Body, Brain and Colony The proposed research neatly falls into three categories: body, brain, and colony.

4. Brain, Body and Colony

5. Body Explore ways to emulate such aerobatic feats in their proposed devices. Achieving autonomous flight requires: - compact high-energy power sources and associated electronics, integrated seamlessly into the ‘body’ of the machine.

6. Body Revolve around construction of a flapping- wing robot. Exploration of several aspects of free flight mechanics and performance.

7. Body

8. Brain One of the most complicated areas of exploration the scientists will undertake will be the creation of: “A suite of artificial “smart” sensors, akin to a bee’s eyes and antennae”.

9. Brain Ultimate aim is: Design the dynamic hardware and software that serves as the device’s ‘brain,’: - Controlling and monitoring flight, - Sensing objects such as fellow devices and other objects, - Coordinating simple decision-making.

10. Brain “The brain incorporates - All of the sensors, - Control (i.e. algorithms and software), - Circuitry (i.e., hardware) to coordinate flight and target identification capabilities of the RoboBees”.

11. Brain

12. Colony To mimic the sophisticated behavior of a real colony of insects will involve: -Sophisticated coordination algorithms, -communications methods (i.e., the ability for individual machines to ‘talk’ to one another and the hive), -Global-to-local programming tools to simulate the ways groups of real bees rely upon one another to scout, forage, and plan.

13. Colony

14. Why Coordination neded? Coordinated behavior by the colony has the potential to dramatically increase effectiveness over each RoboBee operating independently.

15. Practical Applications Autonomously pollinating a field of crops. search and rescue (e.g., in the aftermath of a natural disaster). hazardous environment exploration. Security and Military surveillance. Traffic monitoring.

16. Conclusion In mimicking the physical and behavioral robustness of insect groups by coordinating large numbers of small, agile robots, many applications that have been achieved will be faster, more reliable, and more efficient.

17. References Ho-Yin Chan, Josh Hiu Man Lam, and Wen J. Li, “A Biomimetic Flying Silicon Microchip: Feasibility Study”, Proceedings of the 2004 IEEE, pp 22-26 http://micro.seas.harvard.edu/research.html http://robobees.seas.harvard.edu/