Challenges and Methods in Testing the Remote Agent Planner
The Remote Agent Experiment (RAX) on the Deep Space 1 (DS1) mission was the first time that an artificially intelligent agent controlled a NASA spacecraft.
planning↗
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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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Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed-Autonomy Traffic
Here, this article presents a novel hierarchical speed planning framework for variable speed limits in mixed-autonomy traffic environments, leveraging server-side macroscopic control and vehicle-side microscopic execution. The framework integrates real-time traffic state estimation (TSE) and reinforcement learning (RL)-based control to mitigate congestion and improve traffic flow. A TSE enhancement module combines macroscopic data from sources like INRIX with high-resolution observations from connected autonomous vehicles (CAVs), enabling predictive modeling to address latency and noise. The target speed design module employs kernel smoothing and a buffer zone strategy to optimize traffic density and flow around bottlenecks. The proposed system was validated in the largest open-road test to date with 100 CAVs, demonstrating an overall 8% traffic density decrease, with a specific decrease of 7% upstream, 10% downstream, and a 52% decrease during the congestion formation phase at bottlenecks.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Utilizing Reinforcement Learning to Continuously Improve a Primitive-Based Motion Planner.
Abstract not provided.
Goddard, Zachary↗
Applications of Autonomous Sensor Task Planner for Intelligence, Surveillance and Reconnaissance.
Abstract not provided.
Johnson, Sarah↗
Utilizing Reinforcement Learning to Continuously Improve a Primitive-Based Motion Planner.
Abstract not provided.
Goddard, Zachary↗
Explanation production by expert planners
Although the explanation capability of expert systems is usually listed as one of the distinguishing characteristics of these systems, the explanation facilities of most existing systems are quite primitive. Computer generated explanations are typically produced from canned text or by direct translation of the knowledge structures. Explanations produced in this manner bear little resemblance to those produced by humans for similar tasks. The focus of our research in explanation is the production of justifications for decisions by expert planning systems. An analysis of justifications written by people for planning tasks has been taken as the starting point. The purpose of this analysis is two-fold. First, analysis of the information content of the justifications will provide a basis for deciding what knowledge must be represented if human-like justifications are to be produced. Second, an analysis of the textual organization of the justifications will be used in the development of a mechanism for selecting and organizing the knowledge to be included in a computer-produced explanation. This paper describes a preliminary analysis done of justifications written by people for a planning task. It is clear that these justifications differ significantly from those that would be produced by an expert system by tracing the firing of production rules. The results from the text analysis have been used to develop an augmented phrase structured grammar (APSG) describing the organization of the justifications. The grammar was designed to provide a computationally feasible method for determining textual organization that will allow the necessary information to be communicated in a cohesive manner.
Bridges, Susan↗
Operations mission planner
The findings are documented of the OMP research task, which investigated the applicability of artificial intelligence (AI) technology in support of automated scheduling. The goals of the effort are summarized and the technical accomplishments are highlighted. The OMP task succeeded in identifying how AI technology could be applied and demonstrated an AI-based automated scheduling approach through the OMP prototypes.
Biefeld, Eric↗
A hierarchical planner for space truss assembly
A hierarchical planning paradigm for space truss assemblies is proposed which generates sequences of assembly operations and is suitable for human, teleoperator, and autonomous robotic implementation. Subgoals satisfying geometric (accessibility) and structural (rigidity) constraints are developed using a hierarchical state representation, and special cost functions are used to conduct a search for locally optimal sequences. Results of two case studies involving assemblies with up to 31 nodes and 102 struts are presented.
Mathur, Rajive K.↗
Advanced construction management for lunar base construction - Surface operations planner
The study proposes a conceptual solution and lays the framework for developing a new, sophisticated and intelligent tool for a lunar base construction crew to use. This concept integrates expert systems for critical decision making, virtual reality for training, logistics and laydown optimization, automated productivity measurements, and an advanced scheduling tool to form a unique new planning tool. The concept features extensive use of computers and expert systems software to support the actual work, while allowing the crew to control the project from the lunar surface. Consideration is given to a logistics data base, laydown area management, flexible critical progress scheduler, video simulation of assembly tasks, and assembly information and tracking documentation.
Kehoe, Robert P.↗
A six degree of freedom, plume-fuel optimal trajectory planner for spacecraft proximity operations using an A* node search
Spacecraft proximity operations are complicated by the fact that exhaust plume impingement from the reaction control jets of space vehicles can cause structural damage, contamination of sensitive arrays and instruments, or attitude misalignment during docking. The occurrence and effect of jet plume impingement can be reduced by planning approach trajectories with plume effects considered. An A* node search is used to find plume-fuel optimal trajectories through a discretized six dimensional attitude-translation space. A plume cost function which approximates jet plume isopressure envelopes is presented. The function is then applied to find relative costs for predictable 'trajectory altering' firings and unpredictable 'deadbanding' firings. Trajectory altering firings are calculated by running the spacecraft jet selection algorithm and summing the cost contribution from each jet fired. A 'deadbanding effects' function is defined and integrated to determine the potential for deadbanding impingement along candidate trajectories. Plume costs are weighed against fuel costs in finding the optimal solution. A* convergence speed is improved by solving approach trajectory problems in reverse time. Results are obtained on a high fidelity space shuttle/space station simulation. Trajectory following is accomplished by a six degree of freedom autopilot. Trajectories planned with, and without, plume costs are compared in terms of force applied to the target structure.
Jackson, Mark Charles↗
Balancing Science Objectives and Operational Constraints: A Mission Planner's Challenge
The Air Force minute sensor technology integration (MSTI-3) satellite's primary mission is to characterize Earth's atmospheric background clutter. MSTI-3 will use three cameras for data collection, a mid-wave infrared imager, a short wave infrared imager, and a visible imaging spectrometer. Mission science objectives call for the collection of over 2 million images within the one year mission life. In addition, operational constraints limit camera usage to four operations of twenty minutes per day, with no more than 10,000 data and calibrating images collected per day. To balance the operational constraints and science objectives, the mission planning team has designed a planning process to e event schedules and sensor operation timelines. Each set of constraints, including spacecraft performance capabilities, the camera filters, the geographical regions, and the spacecraft-Sun-Earth geometries of interest, and remote tracking station deconflictions has been accounted for in this methodology. To aid in this process, the mission planning team is building a series of tools from commercial off-the-shelf software. These include the mission manifest which builds a daily schedule of events, and the MSTI Scene Simulator which helps build geometrically correct scans. These tools provide an efficient, responsive, and highly flexible architecture that maximizes data collection while minimizing mission planning time.
Weldy, Michelle↗
Universal Quantification in a Constraint-Based Planner
Constraints and universal quantification are both useful in planning, but handling universally quantified constraints presents some novel challenges. We present a general approach to proving the validity of universally quantified constraints. The approach essentially consists of checking that the constraint is not violated for all members of the universe. We show that this approach can sometimes be applied even when variable domains are infinite, and we present some useful special cases where this can be done efficiently.
Golden, Keith↗
MAPGEN Planner: Mixed-Initiative Activity Planning for the Mars Exploration Rover Mission
This document describes the Mixed-initiative Activity Plan Generation system MAPGEN. The system is be- ing developed as one of the tools to be used during surface operations of NASA's Mars Exploration Rover mission (MER). However, the core technology is general and can be adapted to different missions and applications. The motivation for the system is to better support users that need to rapidly build activity plans that have to satisfy complex rules and fit within resource limits. The system therefore combines an existing tool for activity plan editing and resource modeling, with an advanced constraint-based reasoning and planning framework. The demonstration will show the key capabilities of the automated reasoning and planning component of the system, with emphasis on how these capabilities will be used during surface operations of the MER mission.
Ai-Chang, Mitch↗
An 800 GHz broadband planner Schottky balanced doubler
This paper describes the design, fabrication, assembly, testing, and performance both at room temperature and at cryogenic temperatures.
Schottky multiplier terahertz electronics terahert↗
Test oracle automation for V&V of an autonomous spacecraft's planner
We built automation to assist the software testing efforts associated with the Remote Agent experiment. In particular, our focus was upon introducing test oracles into the testing of the planning and scheduling system component. This summary is intended to provide an overview of the work.
testing test oracles verification validation analy↗
Knowledge Acquisition for the Onboard Planner of an Autonomous Spacecraft
This paper discusses the knowledge acquisition issues involved in transitioning their novel technology in to space flight software, developing the planer in the context of a large software projet and completing the work under a compressed development schedule.
Knowledge Aquisition Deep Space↗
The RadarSAT-MAMM automated mission planner
The RadarSAT Modified Antarctic Mapping Mission (MAMM) ran from September to November 2000. It consisted of over 2400 synthetic aperture radar (SAR) data takes over Antarctica that had to satisfy coverage and other scientific criteria while obeying tight resource and operational constraints. Developing these plans is a time and knowledge intensive effort. It required over a work-year to manually develop a comparable plan for AMM-1, the precursor mission to MAMM. This paper describes the automated mission planning system for MAMM, which dramatically reduced mission-planning costs to just a few workweeks, and enabled rapid generation of 'what-if' scenarios for evaluating mission-design trades. This latter capability informed several critical design decisions and was instrumental in accurately costing the mission.
RadarSAT Modified Antarctic Mapping Mission (MAMM)↗
MSLICE Science Activity Planner for the Mars Science Laboratory Mission
MSLICE (Mars Science Laboratory InterfaCE) is the tool used by scientists and engineers on the Mars Science Laboratory rover mission to visualize the data returned by the rover and collaboratively plan its activities. It enables users to efficiently and effectively search all mission data to find applicable products (e.g., images, targets, activity plans, sequences, etc.), view and plan the traverse of the rover in HiRISE (High Resolution Imaging Science Experiment) images, visualize data acquired by the rover, and develop, model, and validate the activities the rover will perform. MSLICE enables users to securely contribute to the mission s activity planning process from their home institutions using off-the-shelf laptop computers. This software has made use of several plug-ins (software components) developed for previous missions [e.g., Mars Exploration Rover (MER), Phoenix Mars Lander (PHX)] and other technology tasks. It has a simple, intuitive, and powerful search capability. For any given mission, there is a huge amount of data and associated metadata that is generated. To help users sort through this information, MSLICE s search interface is provided in a similar fashion as major Internet search engines. With regard to the HiRISE visualization of the rover s traverse, this view is a map of the mission that allows scientists to easily gauge where the rover has been and where it is likely to go. The map also provides the ability to correct or adjust the known position of the rover through the overlaying of images acquired from the rover on top of the HiRISE image. A user can then correct the rover s position by collocating the visible features in the overlays with the same features in the underlying HiRISE image. MSLICE users can also rapidly search all mission data for images that contain a point specified by the user in another image or panoramic mosaic. MSLICE allows the creation of targets, which provides a way for scientists to collaboratively name features on the surface of Mars. These targets can also be used to convey instrument-pointing information to the activity plan. The software allows users to develop a plan of what they would like the rover to accomplish for a given time period. When developing the plan, the user can input constraints between activities or groups of activities. MSLICE will enforce said constraints and ensure that all mission flight rules are satisfied.
Powell, Mark W.↗