Autonomous Rapid Exploration in Close-Proximity of an Asteroid

TL;DR

The paper advocates a shift from ground-in-the-loop asteroid missions to autonomous, robust GN&C that directly handles environmental uncertainties. It presents a navigation stack based on a batch-sequential estimator using LiDAR, cameras, and IMU data, paired with a Monte Carlo-Lambert guidance and a sliding-mode-based orbital maintenance controller to ensure safe, fuel-efficient operations near small bodies. Through Bennu and Eros case studies and extensive Monte Carlo runs, the authors show that close-proximity insertion and transfers between tight orbits are feasible with modest ΔV budgets (roughly 8–11 m/s in the Bennu/Eros scenarios) and position errors at the meter level, even with substantial uncertainties. The work highlights that autonomous exploration can significantly reduce mission time and cost, though accurate asteroid shape information remains a key factor for performance in tight orbits and suggests future hardware-in-the-loop validation and enhanced onboard shape estimation to fully realize this paradigm.

Abstract

The increasing number of space missions may overwhelm ground support infrastructure, prompting the need for autonomous deep-space guidance, navigation, and control (GN\&C) systems. These systems offer sustainable and cost-effective solutions, particularly for asteroid missions that deal with uncertain environments. This study proposes a paradigm shift from the proposals currently found in the literature for autonomous asteroid exploration, which inherit the conservative architecture from the ground-in-the-loop approach that relies heavily on reducing uncertainties before close-proximity operations. Instead, it advocates for robust guidance and control to handle uncertainties directly, without extensive navigation campaigns. From a series of conservative assumptions, we demonstrate the feasibility of this autonomous GN\&C for robotic spacecraft by using existing technology. It is shown that a bolder operational approach enables autonomous spacecraft to significantly reduce exploration time by weeks or months. This paradigm shift holds great potential for reducing costs and saving time in autonomous missions of the future.

Figures (10)

• Figure 1: Finite-State Machine of the proposed GN$\&$C flight software within the simulation.
• Figure 2: Results for Bennu exploration.
• Figure 3: Results for Eros exploration.
• Figure 4: Results for Eros exploration with a 100 km circular orbit.
• Figure 5: Monte Carlo analysis for Bennu exploration.