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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Improved Path Planning Onboard the Mars Exploration Rovers

A revised version of the AutoNav (autonomous navigation with hazard avoidance) software running onboard each Mars Exploration Rover (MER) affords better obstacle avoidance than does the previous version. Both versions include GESTALT (Grid-based Estimation of Surface Traversability Applied to Local Terrain), a navigation program that generates local-terrain models from stereoscopic image pairs captured by onboard rover cameras; uses this information to evaluate candidate arcs that extend across the terrain from the current rover location; ranks the arcs with respect to hazard avoidance, minimization of steering time, and the direction towards the goal; and combines the rankings in a weighted vote to select an arc, along which the rover is then driven. GESTALT works well in navigating around small isolated obstacles, but tends to fail when the goal is on the other side of a large obstacle or multiple closely spaced small obstacles. When that occurs, the goal seeking votes and hazard avoidance votes conflict severely. The hazard avoidance votes will not allow the rover to drive through the unsafe area, and the waypoint votes will not allow enough deviation from the straight-line path for the rover to get around the hazard. The rover becomes stuck and is unable to reach the goal. The revised version of AutoNav utilizes a global path-planning program, Field D*, to evaluate the cost of traveling from the end of each GESTALT arc to the goal. In the voting process, Field D* arc votes supplant GESTALT goal-seeking arc votes. Hazard avoidance, steering bias, and Field D* votes are merged and the rover is driven a preset distance along the arc with the highest vote. Then new images are acquired and the process as described is repeated until the goal is reached. This new technology allows the rovers to autonomously navigate around much more complex obstacle arrangements than was previously possible. In addition, this improved autonomy enables longer traverses per Sol (a day on Mars), and can make planning drives easier for operators on Earth.

Stentz, Anthony↗
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↗
NASA NTRS2011

Onboard Short Term Plan Viewer

Onboard Short Term Plan Viewer (OSTPV) is a computer program for electronic display of mission plans and timelines, both aboard the International Space Station (ISS) and in ISS ground control stations located in several countries. OSTPV was specifically designed both (1) for use within the limited ISS computing environment and (2) to be compatible with computers used in ground control stations. OSTPV supplants a prior system in which, aboard the ISS, timelines were printed on paper and incorporated into files that also contained other paper documents. Hence, the introduction of OSTPV has both reduced the consumption of resources and saved time in updating plans and timelines. OSTPV accepts, as input, the mission timeline output of a legacy, print-oriented, UNIX-based program called "Consolidated Planning System" and converts the timeline information for display in an interactive, dynamic, Windows Web-based graphical user interface that is used by both the ISS crew and ground control teams in real time. OSTPV enables the ISS crew to electronically indicate execution of timeline steps, launch electronic procedures, and efficiently report to ground control teams on the statuses of ISS activities, all by use of laptop computers aboard the ISS.

Hall, Tim↗
NASA NTRS2020

MEXEC: An Onboard Integrated Planning and Execution Approach for Spacecraft Commanding

The traditional form of spacecraft commanding is with sequences that specify when commands should execute based on a schedule generated on the ground. Some sequences have control logic and event driven responses to increase flexibility, but it is limited. An approach to increase autonomy is to use goal-based planning and commanding. Using this paradigm, intention and behavior is modeled on board the spacecraft. In this paper we describe MEXEC (Multi-mission EXECutive), a multi-mission, task-based, onboard planning and execution software designed specifically to be used as flight software. As a path to infusion for future flight projects, we describe two experiments performed on the ASTERIA CubeSat and testbed that demonstrate that MEXEC can be integrated and used for spacecraft operations and increase robustness and science return compared to the standard sequences that were being used.

Campuzano, Brian↗
NASA NTRS2004

Flight software issues in onboard automated planning: lessons learned on EO-1

This paper focuses on the onboard planner and scheduler CASPER, whose core planning engine is based on the ground system ASPEN. Given the challenges of developing flight software, we discuss several of the issues encountered in preparing the planner for flight, including reducing the code image size, determining what data to place within the engineering telemetry packet, and performing long term planning.

planning↗
NASA NTRS2008

Spatial Coverage Planning for a Planetary Rover

We are developing onboard planning and execution technologies to support the exploration and characterization of geological features by autonomous rovers. In order to generate high quality mission plans, an autonomous rover must reason about the relative importance of the observations it can perform. In this paper we look at the scientific criteria of selecting observations that improve the quality of the area covered by samples. Our approach makes use of a priori information, if available, and allows scientists to mark sub-regions of the area with relative priorities for exploration. We use an efficient algorithm for prioritizing observations based on spatial coverage that allows the system to update observation rankings as new information is gained during execution.

Onboard planning↗
NASA NTRS2008

Spatial Coverage Planning and Optimization for Planetary Exploration

We are developing onboard planning and scheduling technology to enable in situ robotic explorers, such as rovers and aerobots, to more effectively assist scientists in planetary exploration. In our current work, we are focusing on situations in which the robot is exploring large geographical features such as craters, channels or regional boundaries. In to develop valid and high quality plans, the robot must take into account a range of scientific and engineering constraints and preferences. We have developed a system that incorporates multiobjective optimization and planning allowing the robot to generate high quality mission operations plans that respect resource limitations and mission constraints while attempting to maximize science and engineering objectives. An important scientific objective for the exploration of geological features is selecting observations that spatially cover an area of interest. We have developed a metric to enable an in situ explorer to reason about and track the spatial coverage quality of a plan. We describe this technique and show how it is combined in the overall multiobjective optimization and planning algorithm.

autonomy↗
NASA NTRS2003

Autonomous Mission Manager for Rendezvous, Inspection and Mating

To meet cost and safety objectives, space missions that involve proximity operations between two vehicles require a high level of autonomy to successfully complete their missions. The need for autonomy is primarily driven by the need to conduct complex operations outside of communication windows, and the communication time delays inherent in space missions. Autonomy also supports the goals of both NASA and the DOD to make space operations more routine, and lower operational costs by reducing the requirement for ground personnel. NASA and the DoD have several programs underway that require a much higher level of autonomy for space vehicles. NASA's Space Launch Initiative (SLI) program has ambitious goals of reducing costs by a factor or 10 and improving safety by a factor of 100. DARPA has recently begun its Orbital Express to demonstrate key technologies to make satellite servicing routine. The Air Force's XSS-ll program is developing a protoflight demonstration of an autonomous satellite inspector. A common element in space operations for many NASA and DOD missions is the ability to rendezvous, inspect anclJor dock with another spacecraft. For DARPA, this is required to service or refuel military satellites. For the Air Force, this is required to inspect un-cooperative resident space objects. For NASA, this is needed to meet the primary SLI design reference mission of International Space Station re-supply. A common aspect for each of these programs is an Autonomous Mission Manager that provides highly autonomous planning, execution and monitoring of the rendezvous, inspection and docking operations. This paper provides an overview of the Autonomous Mission Manager (AMM) design being incorporated into many of these technology programs. This AMM provides a highly scalable level of autonomous operations, ranging from automatic execution of ground-derived plans to highly autonomous onboard planning to meet ground developed mission goals. The AMM provides the capability to automatically execute the plans and monitor the system performance. In the event of system dispersions or failures the AMM can modify plans or abort to assure overall system safety. This paper describes the design and functionality of Draper's AMM framework, presents concept of operations associated with the use of the AMM, and outlines the relevant features of the flight demonstrations.

Zimpfer, Douglas J.↗
NASA NTRS2007

Spatial Coverage Planning for Exploration Robots

A report discusses an algorithm for an onboard planning and execution technology to support the exploration and characterization of geological features by autonomous rovers. A rover that is capable of deciding which observations are more important relieves the engineering team from much of the burden of attempting to make accurate predictions of what the available rover resources will be in the future. Instead, the science and engineering teams can uplink a set of observation requests that may potentially oversubscribe resources and let the rover use observation priorities and its current assessment of available resources to make decisions about which observations to perform and when to perform them. The algorithm gives the rover the ability to model spatial coverage quality based on data from different scientific instruments, to assess the impact of terrain on coverage quality, to incorporate user-defined priorities among subregions of the terrain to be covered, and to update coverage quality rankings of observations when terrain knowledge changes. When the rover is exploring large geographical features such as craters, channels, or boundaries between two different regions, an important factor in assessing the quality of a mission plan is how the set of chosen observations spatially cover the area of interest. The algorithm allows the rover to evaluate which observation to perform and to what extent the candidate observation will increase the spatial coverage of the plan.

Gaines, Daniel↗
NASA NTRS2021

Concept of Operations for OSIRIS-REx Optical Navigation Image Planning

Optical navigation (OpNav) is a critical subsystem of the OSIRIS-REx asteroid sample return mission, which operated in the vicinity of near-Earth asteroid (101955) Bennu from August 2018 through April 2021. A substantial amount of mission resources across multiple subsystems and institutions is required to ensure that the OpNav data are successfully acquired. The KinetX OpNav team, part of the Flight Dynamics System (FDS), is responsible for performing required analysis to develop the OpNav operations plans; requesting, reviewing and verifying the plans; and ultimately using the image data for critical navigation operations. The FDS team, responsible for the mission navigation, is operated by KinetX Aerospace with management and operations support from NASA’s Goddard Space Flight Center. The Science Processing and Operations Center (SPOC), located at the University of Arizona’s Lunar and Planetary Laboratory, is responsible for generating the planning products for all science and most OpNav data. These plans are integrated into the spacecraft sequences, tested, and commanded by the Mission Support Area (MSA) at Lockheed Martin Space. To ensure mission-critical navigation image data are successfully acquired, the plan is developed through a waterfall of planning cycles over the course of 3 months prior to onboard plan execution. During the initial strategic planning for a mission phase, detailed analysis is performed by the OpNav team to conceptualize the concept of operations (ConOps) for image data collection. This phase OpNav Narrative is included along with other strategic planning documents for the key ground segment stakeholders to review and provide feedback. The detailed OpNav plans get defined in the tactical planning cycle, which spans 8 to 3 weeks before the week-long integrated sequence is executed on-board the spacecraft. During the tactical cycle, the initial OpNav Request is submitted along with the science requests, kicking off development of the science and OpNav plans. Once the initial plan is drafted, interfaces are exercised so that the plan can be reviewed and iterated, if necessary. A rigorous schedule is followed by the planning teams during the implementation cycle, spanning the last 18 days before uplink, to ensure all the necessary integration, testing, and reviewing can occur on time. The development of the OpNav planning ConOps, including responsibilities, interfaces, timelines, and procedures, took extensive collaboration across mission elements and institutions. The process was robust throughout the 137 weeks of continuous Optical Navigation Operations at Bennu, which concluded on April 9th, 2021.

Coralie D. Adam↗
NASA NTRS2005

Robust and Opportunistic Planning for Planetary Exploration

This slide presentation discusses the use of robust planning for rover vehicles to enable planetary exploration. The objective of this work is to use onboard planning, scheduling and execution techniques to enable a rover to take autonomous action to take advantage of new opportunities, and to respond to unexpected problems, and to improve the overall utilization of rover resources.

onboard science analysis↗
NASA NTRS2002

Onboard autonomy on the Three Corner Sat mission

In 2003, the student-built three satellite constellation Three Corner Sat (3CS) Mission will demonstrate onboard autonomy including: science data validation and prioritization, mission re-planning, and robust execution. Future observations will be planned onboard based on the quality of aquired science, available memory and power, and anticipated downlinks. These capabilities will allow 3CS to aquire additional science data if resources are available and to return only the highest quality science data.

Planning scheduling autonomy↗
NASA NTRS2004

Argumentation for coordinating shared activities

There is an increasing need for space missions to be able to collaboratively (and competitively) develop plans both within and across missions. In addition, interacting spacecraft that interleave onboard planning and execution must reach consensus on their commitments to each other prior to execution.

scheduling↗