Engineering topics
Publications and source records attributed to Mutz, D..
We will present an overview of the CLARAty architecture which aims at developing reusable software components for robotic systems.
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This paper presents an overview of the intelligent decison-making capabilities of the CLARAty robotic architecture for autonomy.
This paper describes the mixed-initiative planning system for MAMM, which dramatically reduced mission-planning costs through automation to just a few scenarios for evaluating mission-design trades.
This paper describes an integrated system for coordinating multiple rover behavior with the overall goal of collecting planetary surface data.
This paper presents an overview of a newly developed Coupled Layer Architecture for Robotic Autonomy (CLARAty), which is designed for improving the modularity of system software while more tightly coupling the interaction of autonomy and controls.
We present an AI planning system that automatically generates and evaluates mission plans for specified spacecraft designs.
This paper describes the ASPEN system for automation of planning and scheduling for space mission operations.
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Proposed missions to explore comets and moons will encounter environments that are hostile and unpredictable.
This paper describes a dynamic planning system for coordinating multiple rovers in collecting planetary surface data.
This paper describes a dynamic planning system for coordinating multiple rovers in 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 considers the problem of learning the ranking of a set of stochastic alternatives based upon incomplete information (i.e., a limited number of samples).
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.
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.