Providing Goal-Based Autonomy for Commanding a Spacecraft

A computer program for use aboard a scientific-exploration spacecraft autonomously selects among goals specified in high-level requests and generates corresponding sequences of low-level commands, understandable by spacecraft systems. (As used here, 'goals' signifies specific scientific observations.) From a dynamic, onboard set of goals that could oversubscribe spacecraft resources, the program selects a non-oversubscribing subset that maximizes a quality metric. In an early version of the program, the requested goals are assumed to have fixed starting times and durations. Goals can conflict by exceeding a limit on either the number of separate goals or the number of overlapping goals making demands on the same resource. The quality metric used in this version is chosen to ensure that a goal will never be replaced by another having lower priority. At any time, goals can be added or removed, or their priorities can be changed, and the 'best' goal will be selected. Once a goal has been selected, the program implements a robust, flexible approach to generation of low-level commands: Rather than generate rigid sequences with fixed starting times, the program specifies flexible sequences that can be altered to accommodate run time variations

Online Planning Algorithm

AVA v2 software selects goals for execution from a set of goals that oversubscribe shared resources. The term goal refers to a science or engineering request to execute a possibly complex command sequence, such as image targets or ground-station downlinks. Developed as an extension to the Virtual Machine Language (VML) execution system, the software enables onboard and remote goal triggering through the use of an embedded, dynamic goal set that can oversubscribe resources. From the set of conflicting goals, a subset must be chosen that maximizes a given quality metric, which in this case is strict priority selection. A goal can never be pre-empted by a lower priority goal, and high-level goals can be added, removed, or updated at any time, and the "best" goals will be selected for execution. The software addresses the issue of re-planning that must be performed in a short time frame by the embedded system where computational resources are constrained. In particular, the algorithm addresses problems with well-defined goal requests without temporal flexibility that oversubscribes available resources. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. Thereby enabling shorter response times and greater autonomy for the system under control

Hollywood Free Paper, May/June 1975

https://digitalcommons.fuller.edu/hollywoodfreepaper/1077/thumbnail.jp

Hollywood Free Paper, February 16 1971

https://digitalcommons.fuller.edu/hollywoodfreepaper/1034/thumbnail.jp

Centralized Planning for Multiple Exploratory Robots

A computer program automatically generates plans for a group of robotic vehicles (rovers) engaged in geological exploration of terrain. The program rapidly generates multiple command sequences that can be executed simultaneously by the rovers. Starting from a set of high-level goals, the program creates a sequence of commands for each rover while respecting hardware constraints and limitations on resources of each rover and of hardware (e.g., a radio communication terminal) shared by all the rovers. First, a separate model of each rover is loaded into a centralized planning subprogram. The centralized planning software uses the models of the rovers plus an iterative repair algorithm to resolve conflicts posed by demands for resources and by constraints associated with the all the rovers and the shared hardware. During repair, heuristics are used to make planning decisions that will result in solutions that will be better and will be found faster than would otherwise be possible. In particular, techniques from prior solutions of the multiple-traveling- salesmen problem are used as heuristics to generate plans in which the paths taken by the rovers to assigned scientific targets are shorter than they would otherwise be

Hollywood Free Paper, January 19 1971

https://digitalcommons.fuller.edu/hollywoodfreepaper/1032/thumbnail.jp

Hollywood Free Paper, February 2 1971

https://digitalcommons.fuller.edu/hollywoodfreepaper/1033/thumbnail.jp

Centralized Alert-Processing and Asset Planning for Sensorwebs

A software program provides a Sensorweb architecture for alert-processing, event detection, asset allocation and planning, and visualization. It automatically tasks and re-tasks various types of assets such as satellites and robotic vehicles in response to alerts (fire, weather) extracted from various data sources, including low-level Webcam data. JPL has adapted cons iderable Sensorweb infrastructure that had been previously applied to NASA Earth Science applications. This NASA Earth Science Sensorweb has been in operational use since 2003, and has proven reliability of the Sensorweb technologies for robust event detection and autonomous response using space and ground assets. Unique features of the software include flexibility to a range of detection and tasking methods including those that require aggregation of data over spatial and temporal ranges, generality of the response structure to represent and implement a range of response campaigns, and the ability to respond rapidly