Teams of mobile robots will play a crucial role in future missions to explore the surfaces of extraterrestrial bodies. Setting up infrastructure and taking scientific samples are expensive tasks when operating in distant, challenging, and unknown environments. In contrast to current single-robot space missions, future heterogeneous robotic teams will increase efficiency via enhanced autonomy and parallelization, improve robustness via functional redundancy, as well as benefit from complementary capabilities of the individual robots. In this article, we present our heterogeneous robotic team, consisting of flying and driving robots that we plan to deploy on scientific sampling demonstration missions at a Moon-analogue site on Mt. Etna, Sicily, Italy in 2021 as part of the ARCHES project. We describe the robots' individual capabilities and their roles in two mission scenarios. We then present components and experiments on important tasks therein: automated task planning, high-level mission control, spectral rock analysis, radio-based localization, collaborative multi-robot 6D SLAM in Moon-analogue and Marslike scenarios, and demonstrations of autonomous sample return.
Traditional network localization algorithms contain ranging and localization steps, which have systematic disadvantages. We propose an algorithm dubbed direct particle filter based distributed network localization (DiPNet). A node's location is directly estimated from the received signals, incorporating location uncertainty of neighboring nodes. The propagation effects on DiPNet become insignificant for dense networks, due to the massive-link collective physical layer processing. DiPNet achieves a near-optimal performance with low complexity, which is particularly attractive for realtime dense-network localization.
The Earth's moon is currently an object of interest of many space agencies for unmanned robotic missions within this decade. Besides future prospects for building lunar gateways as support to human space flight, the Moon is an attractive location for scientific purposes. Not only will its study give insight on the foundations of the Solar System but also its location, uncontaminated by the Earth's ionosphere, represents a vantage point for the observation of the Sun and planetary bodies outside the Solar System. Lunar exploration has been traditionally conducted by means of single-agent robotic assets, which is a limiting factor for the return of scientific missions. The German Aerospace Center (DLR) is developing fundamental technologies towards increased autonomy of robotic explorers to fulfil more complex mission tasks through cooperation. This paper presents an overview of past, present and future activities of DLR towards highly autonomous systems for scientific missions targeting the Moon and other planetary bodies. The heritage from the Mobile Asteroid Scout (MASCOT), developed jointly by DLR and CNES and deployed on asteroid Ryugu on 3 October 2018 from JAXA's Hayabusa2 spacecraft, inspired the development of novel core technologies towards higher efficiency in planetary exploration. Together with the lessons learnt from the ROBEX project (2012–2017), where a mobile robot autonomously deployed seismic sensors at a Moon analogue site, this experience is shaping the future steps towards more complex space missions. They include the development of a mobile rover for JAXA's Martian Moons eXploration (MMX) in 2024 as well as demonstrations of novel multi-robot technologies at a Moon analogue site on the volcano Mt Etna in the ARCHES project. Within ARCHES, a demonstration mission is planned from the 14 June to 10 July 2021, 1 during which heterogeneous teams of robots will autonomously conduct geological and mineralogical analysis experiments and deploy an array of low-frequency antennas to measure Jovian and solar bursts. This article is part of a discussion meeting issue ‘Astronomy from the Moon: the next decades'.
Autonomous robotic swarms are envisioned for a variety of sensing applications in space exploration, search-and-rescue and disaster management. An important capability of a swarm is sensing spatio-temporal processes such as radio wave propagation or seismic activities. The spatio-temporal properties of these processes dictate the required sensing position and time accuracy, as well as update rate. A dedicated wireless communication system needs to be jointly designed for swarm information exchange, self-localization and sensing. In this article, we emphasize the role of time in a robotic swarm. We introduce the system ingredients and dive into realistic clock models. Clock models and channel access schemes decisively influence the swarm self-localization and synchronization accuracy, and consequently the swarm sensing performance. Finally, we discuss practical implementation aspects, introduce our developed swarm radio system, and give an outlook on a moon-analogue exploration mission. Siwei Zhang received the B.Sc. in electrical engineering from the Zhejiang University, China, in 2009, the M.Sc. in communication engineering from the Technical University of Munich, Germany, in 2011, and the Dr.-Ing. (Ph.D.) in electrical engineering from the University of Kiel, Germany, in 2020. In 2012, he joined the Institute of Communications and Navigation, German Aerospace Center (DLR), Germany, as a Research Staff Member. His research interests include radio navigation, cooperative positioning and swarm navigation. Robert Pöhlmann received B.Sc. and M.Sc. in electrical engineering and information technology from the Technical University of Munich (TUM), Germany, in 2014 and 2016, respectively. In 2013, he joined the Institute of Communications and Navigation, German Aerospace Center (DLR), Germany, as a Student Trainee, where he became a Research Staff Member in 2016. His current research interests are in the area of statistical signal processing for multi-antenna systems and cooperative localization. Armin Dammann received the Dipl.Ing. (M.Sc.) and Dr.Ing. (Ph.D.
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