APS

Adaptive Problem Solving for Large Scale Scheduling and Resource Allocation Problems task involves the development of Machine Learning Methods to automatically find effective domain-specific scheduler control strategies. It is applied to the domains of spacecraft commanding and to Deep Space Network scheduling problems.

CLEaR

Closed Loop Execution and Recovery is an integrated planning and execution framework for autonomous control of robotic entities. The CLEaR system currently utilizes CASPER and TDL, and focuses on on the use of both near-term reactive behavior and long-term deliberative decision making.

Benchmark Problem Domains

The benchmark problem domains were developed and released in response to the disconnect between the research and application communities in planning and scheduling. The two actual space domains, DATA-CHASER and CX-1, developed at Colorado Space Grant, contain multiple levels of difficulty and simulators corresponding to these levels, in the hopes the the planning and scheduling community will direct research towards more real-world problems.

3CS

Three Corner Satellite is a demonstration of stereo imaging, formation flying and innovative command and data handling, including on-board autonomy + Read More

CX1

Citizen Explorer is a small earth orbiting satellite built and managed by the Colorado Space Grant Consortium.

DS-1

Deep Space 1 The first deep space flight of the New Millenium program will feature advanced software for autonomous operation.

MAMM

Modified Antarctic Mapping Missison The ASPEN planning system automated the mission planning process and provided a fast replanning capability for responding to anomolies during operations.

Autonomous Rover Command Generation

A proof-of-concept prototype for automatic generation of validated rover command sequences from high-level science and engineering activities.

Rocky-7 Rover Science Planning

An intelligent science tool for planetary rover operations.

DSSC

Deep Space Station Controller is an extension to the work performed for the Deep Space Terminal (DS-T) task, part of the Deep Space Network, in the area of track automation. This work utilizes the CLEaR system to provide the capability for robust dynamic desision making and execution management for autonomous DSN ground station operations.

UAVs

Unmanned Air Vehicles consist of integrating JPL planning, diagnostics, and prognostics systems as part of the control architecture for UAVs.

ASIP

Automated SAR Image Processing system uses Artificial Intelligence Planning techniques to automate most fo the steps in image processing of synthetic aperature radar (SAR) images to satisfy science requests

MVP

Multimission VICAR Planner uses Artificial Intelligence Planning techniques to automatically synthesize executable image processing processing procedures to satisfy science requests.