A parametric design method of nanosatellite close-range formation for on-orbit target inspection

This paper proposes an efficient design method for nano satellites formation flying near a large space target to perform ultra-close inspection missions.A parametric model for periodic relative motion between two satellites is firstly proposed through a detailed analysis of the relative orbital dynamics.It is proved that the existing periodic solutions of satellite relative motion such as in-plane 2:1 elliptic and circular periodic relative orbits both belong to the ellipsoid family of periodic relative orbits.The motion planes and their locations and orientations of the general periodic relative orbits are then determined as the analytic functions of the initial relative states.The maximal and minimal distances from the relative orbit to the origin are further analytically calculated too.A formation design algorithm is then proposed for optimal observation of feature points of the target considering various requirements of collision avoidance and observable distance by using this parametric model.Numerical examples about target inspection are introduced to quantitively evaluate and verify the models and methods.The simulation results are well consistent with the theoretical predictions,showing that the design proposed can be potentially applied for future practical on-orbit service missions.

Applying project‐based learning in artificial intelligence and marine discipline:An evaluation study on a robotic sailboat platform

intelligence is penetrating various fields.The demand for interdisciplinary talent is increasingly important,while interdisciplinary educational activities for high school students are lagging behind.Project‐based learning(PBL)in artificial intelligence(AI)and robotic education activities supported by a robotic sailboat platform,the sailboat test arena(STAr),has been shown to popularise AI and robotic knowledge in young students.In the implementation of the programme,PBL was provided for students,and gamification pedagogy was applied to increase participants'learning motivation and engagement.The results show that the proposed STAr‐based programme is capable of delivering the desired knowledge and skills to students at high school levels.The assessment results suggest that most students achieve learning outcomes on average.Students showed more interest in AI and marine disciplines and were willing to participate in more such educational programs.The findings fill the research gap that few existing education platforms have facilitated the teaching and learning of AI and marine disciplines for high school students.