The NASA Ames Planning and Scheduling Group has developed and demonstrated techniques for automated planning, scheduling and control. In addition to extensive technical expertise, the group has extensive experience delivering planning and scheduling software to NASA missions involving ground, flight, and surface operations, across the spectrum of NASA endeavors on Earth, in space, and for planetary exploration.
The planning and scheduling group has developed four core technologies that are publicly available and used within many of the group's other projects:
Project Lead: Leslie Keely-Meindorfer
Desktop Exploration of Remote Terrain (DERT) is a software tool for exploring large Digital Terrain Models (DTMs) in 3D. It aids in understanding topography and spatial relationships of terrain features, as well as performing simple analysis tasks relevant to the planetary science community. DERT simulates the DTM as a virtual world, attempting to stay true to dimension, light, and color. Using a mouse, the user may freely navigate throughout this world, viewing the terrain from any viewpoint.
Project Lead: Michael Iatauro
EUROPA is a framework to model and tackle problems in Planning, Scheduling and Constraint Programming. It has been used in a wide variety of projects within NASA and elswhere.
Project Lead: Chuck Fry
PLEXIL (Plan Execution Interchange Language) is a language for representing plans for automation, accompanied by an execution engine (executive) that implements efficiently the PLEXIL language and can provide interfaces to controlled systems as well as decision support systems.
Project Lead: Alfredo Bencomo
Website: OpenSPIFe Home
The Scheduling and Planning Interface for Exploration (SPIFe) is now an open source framework available on NASA GitHub. SPIFe is an integrated planning and scheduling toolkit based on hundreds of hours of expert observation, use, and refinement of state-of-the-art planning and scheduling technology for several NASA missions; which includes the Mars Exploration Rover, the Phoenix Mars Lander, and the Mars Science Laboratory. It has also been adapted as preflight planning and a real-time analysis console tool that supports all phases of planning on the International Space Station (ISS), as well as several other flight projects and analogs.
Aircraft Diversion Decision Support
Project Lead: J. Benton
On occasion, airlines must divert aircraft from their original destination. Usually this occurs because of weather or unusually high traffic at an airport. Determining which aircraft to divert and where to divert them to requires considering several constraints, such as the connections passengers have on each flight and the expected traffic conditions at alternate airports. Working with other divisions within NASA and airline dispatchers, we are developing decision support tools to help determine aircraft diversion strategies on-the-fly.
Project Lead: Matthew D’ortenzio
Jigsaw is a project whose goal is to deconflict individual communication requests from closely related missions. The result is an optimized integrated request that is presented to the Deep Space Network. The testbed for this project involves three CubeSat missions: BioSentinel, Lunar Flashlight, and Near-Earth Asteroid Scout. These will be among several "piggyback" missions carried on the Exploration Mission 1 (EM-1) unmanned test flight of the Space Launch System (SLS) and the Orion capsule, currently scheduled for late 2018. While the Orion capsule will circle the Moon and return to the Earth, the secondary payload missions will be deployed soon after launch, each with their own objectives and destinations. For the first few days of the mission all of the secondary payloads and the Orion will remain clustered in the same portion of the sky relative to ground-based communications assets. Hence the deployments and any subsequent early-mission critical events will be close together in both space and time, which will present potential conflicts as well as potential synergistic opportunities. The resulting challenging scheduling problem will be addressed by Jigsaw.
Path description for the three cubsat missions
Autonomy Operating System (AOS)
Project Lead: Michael Dalal
This project, comprised of members from several NASA groups, and researchers at several universities, is a feasibility study of how Unmanned Aerial Vehicles (UAVs) might be able to safely and reliably fly autonomously in airspace shared by human-piloted aircraft, and do so specifically through interacting with the Air Traffic Controller (ATC) and observing ATC directives such as clearances in the way required of a human certified pilot. The project is currently conducting test flights with small drones running a suite of interoperating software, both third-party and NASA-developed, including PLEXIL as its high level flight procedure representation and execution system.
Integrated Activity and Traverse Planning
Project Lead: John Bresina
In planning for a rover mission (e.g., MER or MSL), there are two primary tasks: planning where the rover will drive and planning the activities the rover will carry out, primarily when stationary between drives. These two tasks have been typically carried out by separate tools and fairly independently. However, the activities required to achieve mission objectives affect the traverse plan, and the spatial and temporal aspects of the traverse plan affect the activity plan. To demonstrate our research concepts, we are using a prototype system that integrates two existing planning tools: xGDS, which is a traverse planner used on numerous analog missions and field tests, and OpenSPIFe, which has been deployed for use on Lunar and Martian missions (e.g., LASS for the LADEE mission and MSLICE for the Curiosity mission).
Reduced Crew Operations (RCO)
Project Lead: David Smith
The research focuses principally on the creation of Increasingly Autonomous Systems (IAS) and in ground support/control of aircraft which can enhance the pilot’s ability to operate in Reduced Crew Operations (RCO) and Single Pilot Operations (SPO) conditions without any compromise to safety. IAS utilize route planning and risk evaluation to plan diversions for aircrafts under nominal and off-nominal conditions. By closer human-machine coupling, the IAS will complement and augment human performance while handling the enormous data volumes, processing capabilities, and decision speeds that new computing system technologies offer.
Project Lead: Robert Morris
The goal of this project is to validate the feasibility of integrating vehicle autonomy into surface operations at busy airports. Specifically, design and test an aircraft towing vehicle that will, on command, autonomously drive to a gate of a departing aircraft, attach itself, push back from the gate, taxi the aircraft to the assigned runway queue, detach itself, and navigate to a designated staging area or to another aircraft. Also determine the feasibility of a similar scenario for arriving aircraft.
Project Lead: Colin Theodore
The goal is to apply automated planning to the problem of dispatching small UAVs (sUAVs) to search for an object of interest and them track its movements. This requires a combination of path and activity planning. We are using ROSPLan, a PDDL-based planning system, to develop plans to be autonomously executed on the vehicle, using the ROS environment to integrate planning with robotic control.
Unmanned Aircraft System (UAS) and Traffic Management (UTM)
Project Lead: Joseph Rios
UTM system would enable safe and efficient low-altitude airspace operations by providing services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning and re-routing, separation management, sequencing and spacing, and contingency management.
PSG group member participation: Currently, the PSG group member (Minh Do) is participating in various activities within the Vehicles and Surveillance group within the UTM project, ranging from Vehicle Database management, flight data analysis, to building algorithms for weather constraint checking.
IRIS Mission Operations
Project Lead: Jim Strong
The Interface Region Imaging Spectrograph (IRIS) is a NASA Small Explorer Mission to observe how solar material moves, gathers energy, and heats up as it travels through a little-understood region in the sun's lower atmosphere. The spacecraft flies at a near Earth orbit and comes into contact with 4 network locations (referred to as a pass). The IRIS mission operations are to prep the satellite for daily command production which executes during the pass by. The ground data systems is responsible for collecting and analyzing the data before packaging the data off to be used for scientific research. Engineers ensure that the communication between the satellite and ground operations are running throughout the week.
Autonomous Systems and Operations (ASO)
Project Lead: Jeremy Frank
NASA's Autonomous Systems and Operations (ASO) develops advanced technologies for autonomous operation of spacecraft. Recently, the project conducted an empirical investigation of the impact of time delay on today’s mission operations, and of the effect of targeted organizational changes, processes and mission support tools designed to mitigate time-delay related impacts. The products of this study will be employed to create technologies that will be flight validated as part of experiments onboard the International Space Station, and as part of the upcomng Exploration Flight Test of the Orion capsule.
Project Lead: Leslie Keely-Meindorfer
Antares is a tool for visual planning of mission science operations, Antares allows an operations team on earth to develop command sequences for the Mars Science Laboratory (MSL) rover’s science cameras, Mastcam, MAHLI, and MARDI in an interactive 3D simulation of the remote Mars environment.
Quantum Computing for Planning
Project Lead: Minh Do
In this joint project with the NASA Quantum Artitificial Intelligence Laboratory (QuAIL), we investigate different approaches to utilize quantum computing to solve planning and scheduling problems effectively. First, we conduct both theoretical and empirical evaluations of planning and scheduling problems that can be solved more effectively by a quantum computer than a traditional computer. In particular, NASA-relevant planning problems which have certain properties or local search topology that make them suitable for quantum computing algorithms (quantum annealing in particular). Second, we look for novel hybrid algorithms that combine the advantages of both quantum computing and classical computer algorithms and how to utilize those algorithms to effectively solve existing planning and scheduling problems. Moreover, in the reverse direction, we are also start investigating how existing planning algorithms can be used to solve challenging quantum computing problems such as scheduling for quantum circuit implementations.
Emergency Landing Planner for Damaged Aircraft
Project Lead: David Smith
We have built a prototype emergency landing planner that takes the current position, direction, and speed of an aircraft, an estimate of the current flight envelope, weather and airport information, and produces an ordered list of recommended emergency landing sites. The system has been integrated into the cockpit environment in the Advanced Concepts Flight Simulator (ACFS) and used in experiments with commercial pilots.
Optimal Acoustics Trajectory Design for Flight Operations
Project Lead: Robert Morris
As part of the Subsonic Rotary Wing (SRW) project, we are applying planning and optimization techniques to design trajectories for flight operations that minimize ground noise. We will verify these trajectories using a high fidelity noise simulator (Rotorcraft Noise Model) and in flight tests.