A connected network of robots and smart sensors can solve grand challenges in domains such as agronomy, oceanography, and infrastructure monitoring. Robots can collect data from hard-to-reach places at unprecedented spatio-temporal scales. In this talk, I will discuss algorithmic problems that are motivated by applications such as bridge inspection with aerial robots, precision agriculture with aerial and ground robots, and monitoring marine environments with aerial robots and robotic boats. 

I will present our recent work on devising approximation algorithms for data collection with heterogeneous robot teams. In particular, I will discuss our recent efforts aimed towards bridging the gap between algorithmic and field robotics by studying issues of resilience and risk-aware planning in the presence of uncertainty and adversarial attacks/failures.