Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions

Issa A D Nesnas; Benjamin J Hockman; Saptarshi Bandopadhyay; Benjamin J Morrell; Daniel P Lubey; Jacopo Villa; David S Bayard; Alan Osmundson; Benjamin Jarvis; Michele Bersani; Shyam Bhaskaran

doi:10.3389/frobt.2021.650885

Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions

Front Robot AI. 2021 Nov 1:8:650885. doi: 10.3389/frobt.2021.650885. eCollection 2021.

Affiliations

¹ Mobility and Robotics Systems Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States.
² Mission Design and Navigation Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States.
³ Ann and H.J. Smead Aerospace Engineering Sciences Department, University of Colorado Boulder, Boulder, CO, United States.
⁴ Guidance and Control Section, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States.
⁵ University of Southern California, Los Angeles, CA, United States.
⁶ The University of Sydney, Camperdown, NSW, Australia.
⁷ Sant'Anna School of Advanced Studies, Pisa, Italy.

Abstract

Autonomy is becoming increasingly important for the robotic exploration of unpredictable environments. One such example is the approach, proximity operation, and surface exploration of small bodies. In this article, we present an overview of an estimation framework to approach and land on small bodies as a key functional capability for an autonomous small-body explorer. We use a multi-phase perception/estimation pipeline with interconnected and overlapping measurements and algorithms to characterize and reach the body, from millions of kilometers down to its surface. We consider a notional spacecraft design that operates across all phases from approach to landing and to maneuvering on the surface of the microgravity body. This SmallSat design makes accommodations to simplify autonomous surface operations. The estimation pipeline combines state-of-the-art techniques with new approaches to estimating the target's unknown properties across all phases. Centroid and light-curve algorithms estimate the body-spacecraft relative trajectory and rotation, respectively, using a priori knowledge of the initial relative orbit. A new shape-from-silhouette algorithm estimates the pole (i.e., rotation axis) and the initial visual hull that seeds subsequent feature tracking as the body gets more resolved in the narrow field-of-view imager. Feature tracking refines the pole orientation and shape of the body for estimating initial gravity to enable safe close approach. A coarse-shape reconstruction algorithm is used to identify initial landable regions whose hazardous nature would subsequently be assessed by dense 3D reconstruction. Slope stability, thermal, occlusion, and terra-mechanical hazards would be assessed on densely reconstructed regions and continually refined prior to landing. We simulated a mission scenario for approaching a hypothetical small body whose motion and shape were unknown a priori, starting from thousands of kilometers down to 20 km. Results indicate the feasibility of recovering the relative body motion and shape solely relying on onboard measurements and estimates with their associated uncertainties and without human input. Current work continues to mature and characterize the algorithms for the last phases of the estimation framework to land on the surface.

Keywords: autonomous approach and landing; autonomous small-body navigation; pole and shape estimation; small-body autonomy; small-body feature tracking; small-sat autonomy; spacecraft autonomy.