A Maximum Principle is proved which governs solutions to dynamic optimization problems in which the controls driving the system may be impulsive and give rise to discontinuous trajectories. The approach, which involves approximating the problem by a conventional one and using Ekeland’s theorem, is new. It permits us to weaken very considerably the hypotheses under which Maximum Principles for such problems have previously been proved.

Fixed-wing unmanned aerial vehicles (UAVs) can be an essential tool for low-cost aerial surveillance and mapping applications in remote regions. There is, however, a key limitation, which is the fact that low-cost UAVs have limited fuel capacity and, hence, require periodic refueling to accomplish a mission. Moreover, the usual mechanism of commanding the UAV to return to a stationary base station for refueling can result in the fuel wastage and inefficient mission operation time. Alternatively, one strategy could be the use of an unmanned ground vehicle (UGV) as a mobile refueling unit, where the UAV will rendezvous with the UGV for refueling. In order to accurately perform this task in the presence of wind disturbances, we need to determine an optimal trajectory in three-dimensional taking UAV and UGV dynamics and kinematics into account. In this paper, we propose an optimal control formulation to generate a tunable UAV trajectory for rendezvous on a moving UGV that also addresses the possibility of the presence of wind disturbances. By a suitable choice of the value of an aggressiveness index that we introduce in our problem setting, we are able to control the UAV rendezvous behavior. Several numerical results are presented to illustrate the reliability and effectiveness of our approach.

This paper presents the Inter-Module Communication (IMC) protocol, a message-oriented protocol designed and implemented in the Underwater Systems and Technology Laboratory (LSTS) to build interconnected systems of vehicles, sensors and human operators that are able to pursue common goals cooperatively by exchanging real-time information about the environment and updated objectives. IMC abstracts hardware and communication heterogeniety by providing a shared set of messages that can be serialized and transferred over different means. The described protocol contrasts with other existing application level protocols by not imposing or assuming a specific software architecture for client applications. Native support can be automatically generated for different programming languages and/or computer architectures resulting in optimized code which can be used both for networked nodes and also for inter-process and inter-thread communication. The protocol has already been tested throughout various experiments led by LSTS where it has taken care of communications between vehicles, sensors and operator consoles. We are now developing the protocol in the direction of having multi-vehicle cooperation using live data from environmental sensors and mixed-initiative user interaction.