ExoMars 2022 Rover Science Operations Preparations

2021 ◽  
Author(s):  
Elliot Sefton-Nash ◽  
Jorge L. Vago ◽  
Luc Joudrier ◽  
Frederic Haessig ◽  
Adam Williams ◽  
...  
Keyword(s):  
1990 ◽  
Author(s):  
PETER KAHN ◽  
KERRY ERICKSON ◽  
ROBERT BROOKS
Keyword(s):  

Author(s):  
Jianwei Mei ◽  
Yan-Zheng Bai ◽  
Jiahui Bao ◽  
Enrico Barausse ◽  
Lin Cai ◽  
...  

Abstract TianQin is a planned space-based gravitational wave (GW) observatory consisting of three Earth-orbiting satellites with an orbital radius of about $10^5 \, {\rm km}$. The satellites will form an equilateral triangle constellation the plane of which is nearly perpendicular to the ecliptic plane. TianQin aims to detect GWs between $10^{-4} \, {\rm Hz}$ and $1 \, {\rm Hz}$ that can be generated by a wide variety of important astrophysical and cosmological sources, including the inspiral of Galactic ultra-compact binaries, the inspiral of stellar-mass black hole binaries, extreme mass ratio inspirals, the merger of massive black hole binaries, and possibly the energetic processes in the very early universe and exotic sources such as cosmic strings. In order to start science operations around 2035, a roadmap called the 0123 plan is being used to bring the key technologies of TianQin to maturity, supported by the construction of a series of research facilities on the ground. Two major projects of the 0123 plan are being carried out. In this process, the team has created a new-generation $17 \, {\rm cm}$ single-body hollow corner-cube retro-reflector which was launched with the QueQiao satellite on 21 May 2018; a new laser-ranging station equipped with a $1.2 \, {\rm m}$ telescope has been constructed and the station has successfully ranged to all five retro-reflectors on the Moon; and the TianQin-1 experimental satellite was launched on 20 December 2019—the first-round result shows that the satellite has exceeded all of its mission requirements.


2010 ◽  
Author(s):  
Kristin Wirth ◽  
Michael Küppers ◽  
Claire Vallat ◽  
Mike Ashman ◽  
Rita Schulz ◽  
...  
Keyword(s):  

2017 ◽  
Vol 17 (3) ◽  
pp. 247-257 ◽  
Author(s):  
Evan B. Clark ◽  
Nathan E. Bramall ◽  
Brent Christner ◽  
Chris Flesher ◽  
John Harman ◽  
...  

AbstractThe development of algorithms for agile science and autonomous exploration has been pursued in contexts ranging from spacecraft to planetary rovers to unmanned aerial vehicles to autonomous underwater vehicles. In situations where time, mission resources and communications are limited and the future state of the operating environment is unknown, the capability of a vehicle to dynamically respond to changing circumstances without human guidance can substantially improve science return. Such capabilities are difficult to achieve in practice, however, because they require intelligent reasoning to utilize limited resources in an inherently uncertain environment. Here we discuss the development, characterization and field performance of two algorithms for autonomously collecting water samples on VALKYRIE (Very deep Autonomous Laser-powered Kilowatt-class Yo-yoing Robotic Ice Explorer), a glacier-penetrating cryobot deployed to the Matanuska Glacier, Alaska (Mission Control location: 61°42′09.3″N 147°37′23.2″W). We show performance on par with human performance across a wide range of mission morphologies using simulated mission data, and demonstrate the effectiveness of the algorithms at autonomously collecting samples with high relative cell concentration during field operation. The development of such algorithms will help enable autonomous science operations in environments where constant real-time human supervision is impractical, such as penetration of ice sheets on Earth and high-priority planetary science targets like Europa.


2016 ◽  
Vol 125 ◽  
pp. 41-64 ◽  
Author(s):  
Mike Ashman ◽  
Maud Barthélémy ◽  
Laurence O׳Rourke ◽  
Miguel Almeida ◽  
Nicolas Altobelli ◽  
...  
Keyword(s):  

Author(s):  
Carol A. Polanskey ◽  
Steven P. Joy ◽  
Carol A. Raymond ◽  
Marc D. Rayman

Sign in / Sign up

Export Citation Format

Share Document