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Autonomous In-Ice Exploration of the Saturnian Moon Enceladus

机译:土星卫星土卫二的自主冰探索

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The data collected by the Cassini spacecraft provide strong evidence for the existence of liquid water under the ice-covered surface of Saturn's moon Enceladus. For that reason, it is currently one of the most promising candidates to find extraterrestrial life in our solar system. The Enceladus Explorer (EnEx) initiative of the German Aerospace Center proposes a concept for a lander mission to probe that moon for life, which uses one maneuverable melting probe to retrieve a sample from the sub-glacial water reservoir as well as multiple smaller melting probes as navigation aids. In addition to technical challenges, a major prerequisite for the success of that mission is the ability to autonomously navigate through the ice of Enceladus. We present an integrated system for multi-sensor fusion, high-level planning and autonomous decision making, as well as trajectory optimization and optimal control, which aims to solve that challenging task. The sensor fusion module is responsible for localizing the probes as well as creating a map of the environment. It uses an approach based on graph optimization techniques, which simultaneously estimates the position and attitude of all probes in 3-dimensional space. For mapping, an extended formalism for representing uncertainty is utilized, which allows one to distinguish between different causes of uncertainty. Based on that information, the autonomy module decides on the further course of action. It creates a high-level plan in order to reach the mission goal or sub-goals, e.g., improving the localization by taking further measurements. In addition, autonomous fault detection is performed, and if required, the system's behavior is adapted in order to compensate for degraded components or unexpected situations. For realizing the high-level plan, the guidance module computes a trajectory in consideration of different optimality criteria. Finally, a model predictive control algorithm generates and applies the corresponding control
机译:卡西尼号航天器收集的数据为土星卫星恩克拉多斯冰封表面下存在液态水提供了强有力的证据。因此,它目前是在我们的太阳系中寻找地外生命的最有希望的候选者之一。德国航空航天中心的恩克拉多斯探险家(EnEx)计划提出了一个终身探测月球的着陆器任务概念,该任务使用一个可操作的熔化探测器从冰下水库中提取样本,以及多个较小的熔化探测器作为导航辅助设备。除了技术挑战外,该任务成功的一个主要先决条件是能够在恩克拉多斯冰上自主导航。我们提出了一个用于多传感器融合、高级规划和自主决策以及轨迹优化和最优控制的集成系统,旨在解决这一具有挑战性的任务。传感器融合模块负责定位探头,并创建环境地图。它使用一种基于图形优化技术的方法,同时估计三维空间中所有探测器的位置和姿态。对于映射,使用了一种表示不确定性的扩展形式,可以区分不确定性的不同原因。根据这些信息,自治模块决定进一步的行动方案。为了达到任务目标或子目标,它创建了一个高层计划,例如,通过进一步测量来改进本地化。此外,还执行自动故障检测,如果需要,系统的行为也会进行调整,以补偿部件退化或意外情况。为了实现高层计划,制导模块根据不同的优化标准计算弹道。最后,模型预测控制算法生成并应用相应的控制

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