Abstract
Autonomous landing on sloped terrain poses significant challenges for small, lightweight spacecraft, such as rotorcraft and landers. These vehicles have limited processing capability and payload capacity, which makes advanced deep learning methods and heavy sensors impractical. Flying insects, such as bees, achieve remarkable landings with minimal neural and sensory resources, relying heavily on optical flow. By regulating flow divergence, a measure of vertical velocity divided by height, they perform smooth landings in which velocity and height decay exponentially together. However, adapting this bio-inspired strategy for spacecraft landings on sloped terrain presents two key challenges: global flow-divergence estimates obscure terrain inclination, and the nonlinear nature of divergence-based control can lead to instability when using conventional controllers. This paper proposes a nonlinear control strategy that leverages two distinct local flow divergence estimates to regulate both thrust and attitude during vertical landings. The control law is formulated based on Incremental Nonlinear Dynamic Inversion to handle the nonlinear flow divergence. The thrust control ensures a smooth vertical descent by keeping a constant average of the local flow divergence estimates, while the attitude control aligns the vehicle with the inclined surface at touchdown by exploiting their difference. The approach is evaluated in numerical simulations using a simplified 2D spacecraft model across varying slopes and divergence setpoints. Results show that regulating the average divergence yields stable landings with exponential decay of velocity and height, and using the divergence difference enables effective alignment with inclined terrain. Overall, the method offers a robust, low-resource landing strategy that enhances the feasibility of autonomous planetary missions with small spacecraft.
Abstract (translated)
自主着陆在斜坡地形上对小型轻量级航天器（如旋翼飞行器和着陆器）构成了重大挑战。这些车辆的处理能力和载荷容量有限，使得先进的深度学习方法和重型传感器变得不切实际。例如蜜蜂等飞行昆虫，在利用最少的神经和感官资源的情况下，实现了非凡的降落效果，主要依赖于光学流的作用。通过调节流散度（即垂直速度与高度之比），它们能够实现平稳着陆，其中速度和高度呈指数衰减同步下降。然而，将这种仿生策略应用于斜坡地形上的航天器着陆面临着两个关键挑战：全局流散度估计会掩盖地形倾斜，而基于流散度的非线性控制性质会导致传统控制器使用时出现不稳定现象。 本文提出了一种非线性控制策略，该策略利用两种不同的局部流散度估算来在垂直着陆过程中同时调节推力和姿态。这种控制法则基于增量非线性动态反转进行制定，以处理非线性的流散度问题。通过保持本地流散度估计的平均值恒定，推力控制确保平稳下降；而利用这些差异，则可以在接触点时使航天器与倾斜表面对齐的姿态控制得以实现。 这种方法在使用简化2D航天器模型并跨越不同坡度和散度设定点进行数值仿真后进行了评估。结果表明，调节平均流散度可以实现速度和高度呈指数衰减的稳定着陆，并且利用流散度差异可以使航天器与倾斜地形有效对齐。总体而言，该方法提供了一种稳健、低资源消耗的着陆策略，提高了小型航天器自主行星任务的可行性。
URL
https://arxiv.org/abs/2512.04373
