We are interested in developing operational strategies for multiple heterogeneous mobile robots, such as having different average running speeds, payloads, sensors, etc. Our goal is to develop algorithms that find a route for each robot such that given missions are completed by at least one of the robots while the maximum travel cost is minimized. This objective leads to reducing the last job completion time, which is an important goal in many applications. We target the algorithms to be able to produce good approximate solutions within a reasonable computation time so that they are applicable to real-time operations.

So far, we have utilized primal-dual techniques to lighten the computational loads while mathematically approaching the problem, which can lead us to have better solution qualities. Starting from a multiple depot heterogeneous traveling salesman problem with the min-sum objective, we've worked on many variations of problems to deal with more general cases. You can find the most recent publication in the field here.

This research focuses on building a microgrid in an unstructured environment with unique mechanisms and controllers for power connector docking and an active cable deployment system. The robotic team consists of Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) for mapping and power generation.