Flexible path

Abstract: In this paper, a memetic algorithm for global path planning MAGPP of mobile robots is proposed. MAGPP is a synergy of genetic algorithm GA based global path planning and a local path refinement. Particularly, candidate path solutions are represented as GA individuals and evolved with evolutionary operators. In each GA generation, the local path refinement is applied to the GA individuals to rectify and improve the paths encoded. MAGPP is characterised by a flexible path encoding scheme, which is introduced to encode the obstacles bypassed by a path. Both path length and smoothness are considered as fitness evaluation criteria. MAGPP is tested on simulated maps and compared with other counterpart algorithms. The experimental results demonstrate the efficiency of MAGPP and it is shown to obtain better solutions than the other compared algorithms.

Abstract: The future of space exploration will not be limited to sortie-style missions to single destinations. Even in present exploration taking place at the International Space Station in low-Earth orbit, logistics is complicated by flights arriving from five launch sites on Earth. The future challenges of space logistics given complex campaigns of interconnected missions in deep space will require innovative tools to aid planning and conceptual design. This paper presents a modeling framework to evaluate the propulsive and logistics feasibility of space exploration from the macro-logistics perspective, which covers the delivery of elements and resources to support demands generated during exploration. The modeling framework is implemented in a versatile and unifying software tool, SpaceNet, for general space exploration scenario analysis. Four space exploration scenarios are presented as application cases to highlight the applicability of the framework across vastly different scenarios. The first case investigates the resupply of the International Space Station between 2010 and 2015 using 77 missions combining NASA, European Space Agency, Japanese Space Agency, Russian Space Agency, and commercial space transportation. The second case models a lunar outpost build-up consisting of 17 flights to achieve continuous human presence over eight years. The third case models and evaluates a conceptual sortie-style mission to a nearEarth object, 1999 AO10. Finally, the fourth case models a flexible path type human exploration in the vicinity of Mars using a combination of human and tele-operated exploration. Taken together these cases demonstrate the challenges and logistical requirements of future human space exploration campaigns during the period from 20102050 and illustrate the ability of SpaceNet to model and simulate the feasibility of meeting these requirements.

Abstract: Abstract This paper develops a network optimization formulation for dynamic campaign-level space mission planning. Although many past space missions have been designed mainly from a mission-level perspective, a campaign-level perspective will be important for future space exploration. In order to find the optimal campaign-level space transportation architecture, a mixed-integer linear programming (MILP) formulation with a generalized multi-commodity flow and a time-expanded network is developed. Particularly, a new heuristics-based method, a partially static time-expanded network, is developed to provide a solution quickly. The developed method is applied to a case study containing human exploration of a near-Earth object (NEO) and Mars, related to the concept of the Flexible Path. The numerical results show that using the specific combinations of propulsion technologies, in-situ resource utilization (ISRU), and other space infrastructure elements can reduce the initial mass in low-Earth orbit (IMLEO) significantly. In addition, the case study results also show that we can achieve large IMLEO reduction by designing NEO and Mars missions together as a campaign compared with designing them separately owing to their common space infrastructure pre-deployment. This research will be an important step toward efficient and flexible campaign-level space mission planning.