火星群探测和导航

S. Sand, Siwei Zhang, Maximilian Mühlegg, Guillermo P. Falconi, Chen Zhu, T. Krüger, S. Nowak
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引用次数: 29

摘要

我们提出自主机器人群探索,以寻找地外生命的水手谷峡谷系统在火星上。该群由无人地面车辆(ugv)和无人飞行器(uav)组成。关键技术是鲁棒飞行和群体控制算法以及无基础设施的群体导航。群导航使用惯性导航、激光扫描仪、照相机和相对的无线电定位系统。后者采用混合时分多址(TDMA) -频分多址(FDMA)和交错往返时延测距测量。针对TDMA,提出了一种自主分布式时隙同步算法。我们呈现一个最初有10个元素的群体场景,在6.25秒后添加一个元素,直到有25个元素处于活动状态。对于25个群元,每个TDMA时隙只发送8个可能符号中的5个是稳定的,但是对于17个群元,每个时隙只发送8个可能符号时,同步算法是稳定的。在后一种情况下,分布式群导航粒子滤波对于21个群元的精度达到1m以上。
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Swarm exploration and navigation on mars
We propose autonomous robotic swarm exploration to search for extra-terrestrial life in the Valles Marineris canyon system on Mars. The swarm consists of unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs). Key technologies are robust flight and swarm control algorithms as well as infrastructure-less swarm navigation. The swarm navigation uses inertial navigation, laser scanners, cameras, and relative radio positioning systems. The later one employs hybrid time-division multiple access (TDMA) - frequency division multiple access (FDMA) and interleaved round-trip delay ranging measurements. For TDMA, an autonomous distributed slot synchronization algorithm is presented.We present a swarm scenario with initially ten elements, adding one element after 6.25 s, until 25 elements are active. The synchronization algorithm is stable transmitting only five out of eight possible symbols per TDMA slot for 25 swarm elements, but is only stable for 17 swarm elements transmitting all eight symbols per slot. Nevertheless, a distributed swarm navigation particle filter achieves an accuracy of 1m or better for 21 swarm elements in the later case.
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