RTS2 - the Remote Telescope System

RTS2 is an open source observatory manager. It was written from scratch in the C++ language, with portability and modularity in mind. Its driving requirements originated from quick follow-ups of Gamma Ray Bursts. After some years of development it is now used to carry tasks it was originally not intended to carry. This article presents the current development status of the RTS2 code. It focuses on describing strategies which worked as well as things which failed to deliver expected results.Comment: 9 pages, 3 figures, Workshop on Robotic Autonomous Observatories, M\'alaga, Spain, 18-21 May 200

An Integer Linear Programming Solution to the Telescope Network Scheduling Problem

Telescope networks are gaining traction due to their promise of higher resource utilization than single telescopes and as enablers of novel astronomical observation modes. However, as telescope network sizes increase, the possibility of scheduling them completely or even semi-manually disappears. In an earlier paper, a step towards software telescope scheduling was made with the specification of the Reservation formalism, through the use of which astronomers can express their complex observation needs and preferences. In this paper we build on that work. We present a solution to the discretized version of the problem of scheduling a telescope network. We derive a solvable integer linear programming (ILP) model based on the Reservation formalism. We show computational results verifying its correctness, and confirm that our Gurobi-based implementation can address problems of realistic size. Finally, we extend the ILP model to also handle the novel observation requests that can be specified using the more advanced Compound Reservation formalism.Comment: Accepted for publication in the refereed conference proceedings of the International Conference on Operations Research and Enterprise Systems (ICORES 2015

Queue scheduling the Alan Cousins Telescope

The Alan Cousins Telescope is a 0.75-m automatic photoelectric telescope situated at the South African Astronomical Observatory, in Sutherland. The telescope was designed and built to execute a range of photometry programmes, but is used mainly for the long-term monitoring of variable stars. In addition, there is the potential for target-of-opportunity observations of unanticipated events, such as gamma ray bursts, and anticipated events such as occultations. Ultimately the telescope is intended to be a fully robotic telescope with limited operational support needs. Some advance toward this goal has been made by a full hardware interface to allow queue executions of observations. The next phase is the implementation of an automated scheduler that will generate a queue of valid observations for each night of observation. Queue scheduling algorithms are widely used in astronomy and the aim of this dissertation is to present a strawman scheduler that will generate the nightly observation queue. The main design of the scheduler is based on a merit-based system implemented at the STELLA robotic observatory, paired with the scheduling algorithms used by SOFIA. The main drawback of the telescope is that it does not currently accommodate dynamically changing weather conditions. As a consequence, the main scheduling constraints are observation parameters, instrument ability, and for monitoring type observations, observation time window constraints

The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed

Creating an Objective Methodology for Human-Robot Team Configuration Selection

As technology has been advancing and designers have been looking to future applications, it has become increasingly evident that robotic technology can be used to supplement, augment, and improve human performance of tasks. Team members can be combined in various combinations to better utilize their capabilities and skills to create more efficient and diversified operational teams. A primary obstacle to integrating new robotic technology has been the inability to quantitatively compare overall team performance between very different team configurations without limiting the analysis to a few metrics. To-date, mission designers have arbitrarily assigned importance to mission parameters, subjectively limiting the search space. While this has been effective at evaluating individual mission plans, the arbitrary evaluation criteria has made a straightforward comparison between different research projects and ranking scales impossible. The question then becomes how to select an objective set of criteria for any given problem. It is this final question that this research sought to answer. A methodology was developed to facilitate performance comparison amongst heterogeneous human and robot teams. This methodology makes no assumptions about mission priorities or preferences. Instead, it provides an objective, generic, quantitative method to reduce the complexity of the mission designer's decision space. It employs an heuristic, greedy objective reduction algorithm to reduce problem complexity and a multi-objective genetic algorithm to explore the design space. The human-robot team configuration selection problem was utilized as the application that motivated this research. The methodology, however, will be applicable to a wider domain of research. It will provide a structure to enable broader search of the design space, exploration of the differences between performance metrics, and comparison of optimization models that facilitate evaluation of the design options

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments