Autonomously generating operations sequences for a Mars rover using AI-based planning

R. Sherwood, A. Mishkin, T. Estlin, Steve Ankuo Chien, P. Backes, J. Norris, B. Cooper, S. Maxwell, G. Rabideau
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引用次数: 8

Abstract

This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences. This prototype is based on ASPEN (Automated Scheduling and Planning Environment). This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute: within resource constraints and satisfy flight rules. An automated planning and scheduling system encodes rover design knowledge and uses the search and reasoning techniques to automatically generate low-level command sequences while respecting the rover operability constraints. This prototype planning system has been field-tested using the Rocky-7 rover at JPL, and will be field-tested on more complex rovers to prove its effectiveness before transferring the technology to flight operations for an upcoming NASA mission. The goal-driven commanding of planetary rovers greatly reduces the requirements for highly skilled rover engineering personnel. This in turn greatly reduces mission operations costs and permits a faster response to changes in rover states.
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基于人工智能规划的火星探测器自主生成操作序列
本文讨论了一种基于地面自动生成经过验证的漫游者命令序列的概念验证原型。这个原型是基于ASPEN(自动调度和计划环境)。这种基于人工智能(AI)的计划和调度系统将自动生成一个命令序列,该命令序列将在资源限制下执行,并满足飞行规则。自动规划和调度系统对漫游车设计知识进行编码,并使用搜索和推理技术在尊重漫游车可操作性约束的情况下自动生成低级命令序列。这个原型规划系统已经在JPL的Rocky-7漫游者上进行了实地测试,并将在更复杂的漫游者上进行实地测试,以证明其有效性,然后将技术转移到即将到来的NASA任务的飞行操作中。行星漫游者的目标驱动指挥大大降低了对高技能漫游者工程人员的要求。这反过来又大大降低了任务的运行成本,并允许更快地响应月球车状态的变化。
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