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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Scaling Up Decision Theoretic Planning to Planetary Rover Problems

Because of communication limits, planetary rovers must operate autonomously during consequent durations. The ability to plan under uncertainty is one of the main components of autonomy. Previous approaches to planning under uncertainty in NASA applications are not able to address the challenges of future missions, because of several apparent limits. On another side, decision theory provides a solid principle framework for reasoning about uncertainty and rewards. Unfortunately, there are several obstacles to a direct application of decision-theoretic techniques to the rover domain. This paper focuses on the issues of structure and concurrency, and continuous state variables. We describes two techniques currently under development that address specifically these issues and allow scaling-up decision theoretic solution techniques to planetary rover planning problems involving a small number of goals.

Meuleau, Nicolas↗
NASA NTRS2008

Pattern-Recognition System for Approaching a Known Target

A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the lander.

Huntsberger, Terrance↗
NASA NTRS2004

Autonomous Navigation Results from the Mars Exploration Rover (MER) Mission

In January, 2004, the Mars Exploration Rover (MER) mission landed two rovers, Spirit and Opportunity, on the surface of Mars. Several autonomous navigation capabilities were employed in space for the first time in this mission. ]n the Entry, Descent, and Landing (EDL) phase, both landers used a vision system called the, Descent Image Motion Estimation System (DIMES) to estimate horizontal velocity during the last 2000 meters (m) of descent, by tracking features on the ground with a downlooking camera, in order to control retro-rocket firing to reduce horizontal velocity before impact. During surface operations, the rovers navigate autonomously using stereo vision for local terrain mapping and a local, reactive planning algorithm called Grid-based Estimation of Surface Traversability Applied to Local Terrain (GESTALT) for obstacle avoidance. ]n areas of high slip, stereo vision-based visual odometry has been used to estimate rover motion, As of mid-June, Spirit had traversed 3405 m, of which 1253 m were done autonomously; Opportunity had traversed 1264 m, of which 224 m were autonomous. These results have contributed substantially to the success of the mission and paved the way for increased levels of autonomy in future missions.

autonomous↗
NASA NTRS2011

The Traverse Planning Process for the Drats 2010 Analog Field Simulations

Traverse planning concentrates on optimizing the science return within the overall objectives of planetary surface missions or their analog field simulations. Such simulations were conducted in the San Francisco Volcanic Field, northern Arizona, from Aug. 26 to Sept 17, 2010 and involved some 200 individuals in the field, with some 40 geoscientists composing the science team. The purpose of these Desert Research and Technology Studies (DRATS) is to exercise and evaluate developmental hardware, software and operational concepts in a mission-like, fully-integrated, setting under the direction of an onsite Mobile Mission Control Center(MMCC). DRATS 2010 focused on the simultaneous operation of 2 rovers, a historic first. Each vehicle was manned by an astronaut-commander and an experienced field geologist. Having 2 rovers and crews in the field mandated substantially more complex science and mission control operations compared to the single rover DRATS tests of 2008 and 2009, or the Apollo lunar missions. For instance, the science support function was distributed over 2 "back rooms", one for each rover, with both "tactical" teams operating independently and simultaneously during the actual traverses. Synthesis and integration of the daily findings and forward planning for the next day(s) was accomplished overnight by yet another "strategic" science team.

Horz, Friedrich↗
NASA NTRS2014

Results from Testing Crew-Controlled Surface Telerobotics on the International Space Station

During Summer 2013, the Intelligent Robotics Group at NASA Ames Research Center conducted a series of tests to examine how astronauts in the International Space Station (ISS) can remotely operate a planetary rover. The tests simulated portions of a proposed lunar mission, in which an astronaut in lunar orbit would remotely operate a planetary rover to deploy a radio telescope on the lunar far side. Over the course of Expedition 36, three ISS astronauts remotely operated the NASA "K10" planetary rover in an analogue lunar terrain located at the NASA Ames Research Center in California. The astronauts used a "Space Station Computer" (crew laptop), a combination of supervisory control (command sequencing) and manual control (discrete commanding), and Ku-band data communications to command and monitor K10 for 11 hours. In this paper, we present and analyze test results, summarize user feedback, and describe directions for future research.

robotics↗
NASA NTRS1974

A conceptual design and operational characteristics for a Mars rover for a 1979 or 1981 Viking science mission

The feasibility of a small Mars rover for use on a 1979 or 1981 Viking mission was studied and a preliminary design concept was developed. Three variations of the concept were developed to provide comparisons in mobility and science capability of the rover. Final masses of the three rover designs were approximately 35 kg, 40 kg, and 69 kg. The smallest rover is umbilically connected to the lander for power and communications purposes whereas the larger two rovers have secondary battery power and a 2-way very high frequency communication link to the lander. The capability for carrying Viking rovers (including development system) to the surface of Mars was considered first. It was found to be feasible to carry rovers of over 100 kg. Virtually all rover systems were then studied briefly to determine a feasible system concept and a practical interface with the comparable system of a 1979 or 1981 lander vehicle.

Darnell, W. L.↗
NASA NTRS1990

Design of a Mars rover and sample return mission

The design of a Mars Rover Sample Return (MRSR) mission that satisfies scientific and human exploration precursor needs is described. Elements included in the design include an imaging rover that finds and certifies safe landing sites and maps rover traverse routes, a rover that operates the surface with an associated lander for delivery, and a Mars communications orbiter that allows full-time contact with surface elements. A graph of MRSR candidate launch vehice performances is presented.

Bourke, Roger D.↗
NASA NTRS2005

Mixed-Initiative Planning in MAPGEN: Capabilities and Shortcomings

MAPGEN (Mixed-initiative Activity Plan GENerator) is a mixed-initiative system that employs automated constraint-based planning, scheduling, and temporal reasoning to assist the Mars Exploration Rover mission operations staff in generating the daily activity plans. This paper describes the mixed-initiative capabilities of MAPGEN, identifies shortcomings with the deployed system, and discusses ongoing work to address some of these shortcomings.

Bresina, John L.↗
NASA NTRS2003

Learning and planning for Mars Rover science

In this paper, we describe the OASIS system, which provides autonomous capabilities for dynamically pursuing these science-collection opportunities during long-range rover traverses.

data analysis planning autonomous rover operations↗
NASA NTRS2001

A tool for autonomous ground-based rover planning

This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from high-level science and engineering activities.

automated planning scheduling rover operations art↗
NASA NTRS2004

Onboard planning for geological investigations using a rover team

This paper describes an integrated system for coordinating multiple rover behavior with the overall goal of collecting planetary surface data. The Multi-Rover Integrated Science Understanding System (MISUS) combines techniques from planning and scheduling with machine learning to perform autonomous scientific exploration with cooperating rovers.

scheduling↗