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Dan Scharf

Publications and source records attributed to Dan Scharf.

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Enhancing Fault-Tolerant Space Computing: Guidance Navigation and Control (GNC) and Landing Vision System (LVS) Implementations on Next-Gen Multi-Core Processors

Future planetary exploration missions demand high-performance, fault-tolerant computing to enable autonomous Guidance, Navigation, and Control (GNC) and Lander Vision System (LVS) operations during Entry, Descent, and Landing (EDL). This paper evaluates the deployment of GNC and LVS algorithms on next-generation multi-core processors--HPSC, Snapdragon VOXL2, and AMD Xilinx Versal--demonstrating up to 15x speedup for LVS image processing and over 250x speedup for Guidance for Fuel-Optimal Large Divert (GFOLD) trajectory optimization compared to legacy spaceflight hardware. To ensure computational reliability, we present ARBITER (Asynchronous Redundant Behavior Inspection for Trusted Execution and Recovery), a Multi-Core Voting (MV) mechanism that performs real-time fault detection and correction across redundant cores. ARBITER is validated in both static optimization tasks (GFOLD) and dynamic closed-loop control (Attitude Control System). A fault injection study further identifies the gradient computation stage in GFOLD as the most sensitive to bit-level errors, motivating selective protection strategies and vector-based output arbitration. This work establishes a scalable and energy-efficient architecture for future missions, including Mars Sample Return, Enceladus Orbilander, and Ceres Sample Return, where onboard autonomy, low latency, and fault resilience are critical.

cs.RO

Autonomy in the Real-World: Autonomous Trajectory Planning for Asteroid Reconnaissance via Stochastic Optimization

This paper presents the development and evaluation of an optimization-based autonomous trajectory planning algorithm for the asteroid reconnaissance phase of a deep-space exploration mission. The reconnaissance phase is a low-altitude flyby to collect detailed information around a potential landing site. Although such autonomous deep-space exploration missions have garnered considerable interest recently, state-of-the-practice in trajectory design involves a time-intensive ground-based open-loop process that forward propagates multiple trajectories with a range of initial conditions and parameters to account for uncertainties in spacecraft knowledge and actuation. In this work, we introduce a stochastic trajectory optimization-based approach to generate trajectories that satisfy both the mission and spacecraft safety constraints during the reconnaissance phase of the Deep-space Autonomous Robotic Explorer (DARE) mission concept, which seeks to travel to and explore a near-Earth object autonomously, with minimal ground intervention. We first use the Multi-Spacecraft Concept and Autonomy Tool (MuSCAT) simulation framework to rigorously validate the underlying modeling assumptions for our trajectory planner and then propose a method to transform this stochastic optimal control problem into a deterministic one tailored for use with an off-the-shelf nonlinear solver. Finally, we demonstrate the efficacy of our proposed algorithmic approach through extensive numerical experiments and show that it outperforms the state-of-the-practice benchmark used for representative missions.

physics.space-ph

Starshade formation flying I: optical sensing

A key challenge for starshades is formation flying. To successfully image exoplanets, the telescope boresight and starshade must be aligned to ~1 m at separations of tens of thousands of kilometers. This challenge has two parts: first, the relative position of the starshade with respect to the telescope must be sensed; and second, sensor measurements must be combined with a control law to keep the two spacecraft aligned in the presence of gravitational and other disturbances. In this work, we present an optical sensing approach using a pupil imaging camera in a 2.4-m telescope that can measure the relative spacecraft bearing to a few centimeters in 1 s, much faster than any relevant dynamical disturbances. A companion paper will describe how this sensor can be combined with a control law to keep the two spacecraft aligned with minimal interruptions to science observations.

astro-ph.IM

The Habitable Exoplanet Observatory (HabEx) Mission Concept Study Interim Report

For the first time in human history, technologies have matured sufficiently to enable a mission capable of discovering and characterizing habitable planets like Earth orbiting sunlike stars other than the Sun. At the same time, such a platform would enable unique science not possible from ground-based facilities. This science is broad and exciting, ranging from new investigations of our own solar system to a full range of astrophysics disciplines. The Habitable Exoplanet Observatory, or HabEx, is one of four studies currently being undertaken by NASA in preparation for the 2020 Astrophysics Decadal Survey. HabEx has been designed to be the Great Observatory of the 2030s, with community involvement through a competed and funded Guest Observer (GO) program. This interim report describes the HabEx baseline concept, which is a space-based 4-meter diameter telescope mission concept with ultraviolet (UV), optical, and near-infrared (near-IR) imaging and spectroscopy capabilities. More information on HabEx can be found at https://www.jpl.nasa.gov/habex

astro-ph.IM