Literature DB >> 33157897

AEGIS autonomous targeting for ChemCam on Mars Science Laboratory: Deployment and results of initial science team use.

R Francis1, T Estlin2, G Doran2, S Johnstone3, D Gaines2, V Verma2, M Burl2, J Frydenvang4, S Montaño3, R C Wiens3, S Schaffer, O Gasnault5, L DeFlores2, D Blaney2, B Bornstein2.   

Abstract

Limitations on interplanetary communications create operations latencies and slow progress in planetary surface missions, with particular challenges to narrow-field-of-view science instruments requiring precise targeting. The AEGIS (Autonomous Exploration for Gathering Increased Science) autonomous targeting system has been in routine use on NASA's Curiosity Mars rover since May 2016, selecting targets for the ChemCam remote geochemical spectrometer instrument. AEGIS operates in two modes; in autonomous target selection, it identifies geological targets in images from the rover's navigation cameras, choosing for itself targets that match the parameters specified by mission scientists the most, and immediately measures them with ChemCam, without Earth in the loop. In autonomous pointing refinement, the system corrects small pointing errors on the order of a few milliradians in observations targeted by operators on Earth, allowing very small features to be observed reliably on the first attempt. AEGIS consistently recognizes and selects the geological materials requested of it, parsing and interpreting geological scenes in tens to hundreds of seconds with very limited computing resources. Performance in autonomously selecting the most desired target material over the last 2.5 kilometers of driving into previously unexplored terrain exceeds 93% (where ~24% is expected without intelligent targeting), and all observations resulted in a successful geochemical observation. The system has substantially reduced lost time on the mission and markedly increased the pace of data collection with ChemCam. AEGIS autonomy has rapidly been adopted as an exploration tool by the mission scientists and has influenced their strategy for exploring the rover's environment.
Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Entities:  

Year:  2017        PMID: 33157897     DOI: 10.1126/scirobotics.aan4582

Source DB:  PubMed          Journal:  Sci Robot        ISSN: 2470-9476


  2 in total

Review 1.  Mission Overview and Scientific Contributions from the Mars Science Laboratory Curiosity Rover After Eight Years of Surface Operations.

Authors:  Ashwin R Vasavada
Journal:  Space Sci Rev       Date:  2022-04-05       Impact factor: 8.943

2.  Towards global flood mapping onboard low cost satellites with machine learning.

Authors:  Gonzalo Mateo-Garcia; Joshua Veitch-Michaelis; Lewis Smith; Silviu Vlad Oprea; Guy Schumann; Yarin Gal; Atılım Güneş Baydin; Dietmar Backes
Journal:  Sci Rep       Date:  2021-03-31       Impact factor: 4.379

  2 in total

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