Lessoned learned deploying space planning systems
This article describes a number of lessons learned in deploying automated planning and scheduling systems for space applications at the Jet Propulsion Laboratory.
Engineering topics
Publications and source records attributed to Estlin, T..
This article describes a number of lessons learned in deploying automated planning and scheduling systems for space applications at the Jet Propulsion Laboratory.
In this paper, we describe the three major areas for autonomous systems for space exploration: free-flying spacecraft, planetary rovers, and ground communications stations.
This paper compares and contrasts several coordination schemes for a system that continuously plans to control collections of rovers (or spacecraft) using collective mission goals, instead of goals or command sequences for each spacecraft.
Explore the source record for details and available documents.
This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from high-level science and engineering activities.
This paper describes and evaluates three methods for coordinating multiple agents.
This paper describes the ASPEN system for automation of planning and scheduling for space mission operations.
This paper will discuss a proof-of-concept prototype for automatic generation of validated rover command sequences from high-level science and engineering activities.
This paper describes a dynamic planning system for coordinating multiple rovers in collecting planetary surface data.
This paper describes and evaluates three methods for coordinating mutiple agents.
This paper describes a dynamic planning system for coordinating multiple rovers in collecting planetary surface data.
This paper describes an integrated system for coordinating multiple rover behavior with the overall goal of collecting planetary surface data.
The paper presents a rover execution architecture for controlling multiple, cooperating rovers. The overall goal of this architecture is to coordinate multiple rovers in performing complex tasks for planetary science.
This paper describes an architecture for an autonomous deep space tracking station (DS-T).
This paper describes the application of Artificial Intelligence planning techniques to the problem of antenna track plan generation for a NASA Deep Space communications Station.
Robust navigation through rocky terrain by small mobile robots is important for maximizing science return from upcoming missions to Mars.
In this paper, we describe how rover command generation can be automated to help relieve some of the burden on human operators.
This paper describes an architecture for an autonomous Deep Space Tracking Station (DS-T).