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The Korean National Space Council recently released “Mars Exploration 2045” as part of its future strategic plan. The operations for a Mars explorer can be defined based on domestically available capabilities, such as ground operations, launch, in-space transport and deep space link. Accordingly, all of our exploration scenarios start from the Naro space center, and the pathway to Mars is optimized using an objective function that minimizes the required ∆V. In addition, the entire phase of Mars orbit insertion should remain in contact with our deep space antennas, a measure that is imposed as an operational constraint. In this study, a pattern search method is adopted, as it can handle a nonlinear problem without relying on the derivatives of the objective function, and optimal trajectories are generated on a daily basis for a 15-day launch period. The robustness of this direct search method is confirmed by consistently converged solutions showing, in particular, that the ascending departure requires slightly less ∆V than the descending departure on the order of 10 m/s. Subsequently, mass estimates are made for a Mars orbiter and a kick stage to determine if the desired ∆V is achievable with our eco-friendly in-space propulsion system when launched from our indigenous launch vehicle, KSLV-II.

Large-scale monitoring systems have seen rapid development in recent years. Wireless sensor networks (WSN), composed of thousands of sensing, computing and communication nodes, form the backbone of such systems. Integration with unmanned aerial vehicles (UAVs) leads to increased monitoring area and to better overall performance. This paper presents a hybrid UAV-WSN network which is self-configured to improve the acquisition of environmental data across large areas. A prime objective and novelty of the heterogeneous multi-agent scheme proposed here is the optimal generation of reference trajectories, parameterized after inter- and intra-line distances. The main contribution is the trajectory design, optimized to avoid interdicted regions, to pass near predefined way-points, with guaranteed communication time, and to minimize total path length. Mixed-integer description is employed into the associated constrained optimization problem. The second novelty is the sensor localization and clustering method for optimal ground coverage taking into account the communication information between UAV and a subset of ground sensors (i.e., the cluster heads). Results show improvements in both network and data collection efficiency metrics by implementing the proposed algorithms. These are initially evaluated by means of simulation and then validated on a realistic WSN-UAV test-bed, thus bringing significant practical value.