  We study a chance-constrained variant of the cooperative aerial-ground
vehicle routing problem, in which an Unmanned Aerial Vehicle (UAV) with limited
battery capacity and an Unmanned Ground Vehicle (UGV) that can also act as a
mobile recharging station need to jointly accomplish a mission such as
monitoring a set of points. Due to the limited battery capacity of the UAV, two
vehicles sometimes have to deviate from their task to rendezvous and recharge
the UAV\@. Unlike prior work that has focused on the deterministic case, we
address the challenge of stochastic energy consumption of the UAV\@. We are
interested in finding the optimal policy that decides when and where to
rendezvous such that the expected travel time of the UAV is minimized and the
probability of running out of charge is less than a user-defined tolerance. We
formulate this problem as a Chance Constrained Markov Decision Process (CCMDP).
To the best knowledge of the authors, this is the first CMDP-based formulation
for the UAV-UGV routing problems under power consumption uncertainty. We adopt
a Linear Programming (LP) based approach to solve the problem optimally. We
demonstrate the effectiveness of our formulation in the context of an
Intelligence Surveillance and Reconnaissance (ISR) mission.

Robotics;Systems and Control;Systems and Control