The goal of this project is to leverage and improve upon the capabilities of honey bees as agricultural pollinators by incorporating them into Bio-Cyber Physical systems. Rapid advances are needed to aid a dwindling agricultural workforce, increase crop yield to sustain the growing population, and provide targeted crop care to limit the need for broad pesticide treatments. These challenges may well be addressed by autonomous mobile robots and sensor networks; unfortunately, agricultural landscapes represent vast, complex, and dynamic environments that complicate long term operation.

In this project, we seek to apply principles from the field of programming languages to distributed robotics. The essence of programming languages is to design simple APIs that support compositional reasoning. We embrace that philosophy through tools from programming languages such as type theory and proof assistants to produce correct-by-construction programs that control teams of robots coordinating their actions to achieve complex tasks.

The objective of this project is to improve the performance of autonomous systems in dynamic environments by integrating perception, planning paradigms, learning, and databases. For the next generation of autonomous systems to be truly effective in terms of tangible performance improvements (e.g., long-term operations, complex and rapidly changing environments), a new level of intelligence must be attained.