Future exploration tasks of small bodies will need to sample or visit multiple points on the target to obtain more scientific returns, requiring rovers to have the ability to hop on a small body surface. This paper proposes an approach to generate a desensitized optimal trajectory for hopping rovers, aiming at reducing the sensitivity of hopping trajectory in the presence of uncertainties. Firstly, considering parameter uncertainties and initial state errors, analytical expressions of optimal initial states are derived on a planar scene, based on ballistic dynamics. Then, similar methods are developed in both uphill and downhill cases of inclined scenes. Subsequently, the desensitization performance of long-distance hopping trajectory is analyzed under single-hop, identical, and non-identical N-hop strategies. To facilitate the application of the proposed analytical solution to the simulated surface environment of small bodies, a prediction-correction procedure is presented. Finally, Monte Carlo simulations are carried out to verify the effectiveness of the proposed methods. The results indicate that the sensitivity of the hopping trajectory to uncertainties can be effectively diminished by employing the desensitized optimal trajectory and multiple hopping strategy.
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