Chien, Steve


Embedding a Scheduler in Execution for a Planetary Rover

AAAI Conferences

Scheduling often takes place in the context of execution. This reality drives several key design decisions: (1) when to invoke (re) scheduling, (2) what to do when the scheduler is running, and (3) how to use the schedule to execute scheduled activities. We define these design decisions theoretically in the context of the embedded scheduler and practically in the context of the design of an embedded scheduler for a planetary rover. We use the concept of a commit window to enable execution to use the previously generated schedule while (re) scheduling. We define the concepts of fixed cadence, event driven, and hybrid scheduling to control invocation of (re) scheduling. We define the concept of flexible execution to enable execution of the generated schedule to be adaptive within the response cycle of the scheduler. We present empirical results from both synthetic and planetary rover scheduling and execution model data that documents the effectiveness of these techniques at enabling the scheduler to take advantage of execution opportunities to complete activities earlier.


Planning and Control of Marine Floats in the Presence of Dynamic, Uncertain Currents

AAAI Conferences

We address the control of a vertically profiling float using ocean-model-based predictions of future currents. While these problems are in reality continuous control problems, we solve them by searching a discrete space of future actions. Additionally, while the environment is a continuous space, the ocean model we use is a discrete cell-based model. We show that even with an imperfect model of ocean currents, planning in the ocean current model can significantly improve results for a specific problem of controlling a vertically profiling float when a trade-off between remaining at the same location as a virtual mooring and collecting more data with more profiles is available. We also present anecdotal data from an April 2015 deployment of EM-APEX floats.


Active Control of Marine Vehicles in the Presence of Strong, Dynamic, Uncertain Currents

AAAI Conferences

We address the control of a vertically profiling float us- ing ocean-model-based predictions of future currents. While these problems are in reality continuous control problems, we solve them by searching a discrete space of future actions. Additionally, while the environment is a continuous space, the ocean model we use is a discrete cell-based model. We show that even with an imperfect model of ocean currents, planning in the ocean current model can significantly improve results for a specific problem of controlling a vertically profiling float when trading off remaining at the same location as a virtual mooring and collecting more data with more profiles.


Activity-based Scheduling of Science Campaigns for the Rosetta Orbiter

AAAI Conferences

Rosetta is a European Space Agency (ESA) cornerstone mission that entered orbit around the comet 67P/Churyumov-Gerasimenko in August 2014 and will escort the comet for a 1.5 year nominal mission offering the most detailed study of a comet ever undertaken by humankind. The Rosetta orbiter has 11 scientific instruments (4 remote sensing) and the Philae lander to make complementary measurements of the comet nucleus, coma (gas and dust), and surrounding environment. The ESA Rosetta Science Ground Segment has developed a science scheduling system that includes an automated scheduling capability to assist in developing science plans for the Rosetta Orbiter. While automated scheduling is a small portion of the overall Science Ground Segment (SGS) as well as the overall scheduling system, this paper focuses on the automated and semi-automated scheduling software (called ASPEN-RSSC) and how this software is used.


Space Applications of Artificial Intelligence

AI Magazine

We are pleased to introduce the space application issue articles in this issue of AI Magazine. The exploration of space is a testament to human curiosity and the desire to understand the universe that we inhabit. As many space agencies around the world design and deploy missions, it is apparent that there is a need for intelligent, exploring systems that can make decisions on their own in remote, potentially hostile environments. At the same time, the monetary cost of operating missions, combined with the growing complexity of the instruments and vehicles being deployed, make it apparent that substantial improvements can be made by the judicious use of automation in mission operations.


Space Applications of Artificial Intelligence

AI Magazine

We are pleased to introduce the space application issue articles in this issue of AI Magazine. The exploration of space is a testament to human curiosity and the desire to understand the universe that we inhabit. As many space agencies around the world design and deploy missions, it is apparent that there is a need for intelligent, exploring systems that can make decisions on their own in remote, potentially hostile environments. At the same time, the monetary cost of operating missions, combined with the growing complexity of the instruments and vehicles being deployed, make it apparent that substantial improvements can be made by the judicious use of automation in mission operations.



Preface

AAAI Conferences

The papers in this proceedings present the latest advances in the field of automated planning and scheduling, ranging in scope from theoretical analyses of planning and scheduling problems and processes, to new algorithms for planning and scheduling under various constraints and assumptions, and the empirical evaluation of planning and scheduling techniques. They reflect recent research trends in subareas such as optimal planning, probabilistic and nondeterministic planning, path planning, multiagent planning, and new developments in heuristics and their analysis for planning algorithms.