Titlebook: Robotics Research; Aude Billard,Tamim Asfour,Oussama Khatib Conference proceedings 2023 The Editor(s) (if applicable) and The Author(s), u

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Lawrence Yunliang Chen,Huang Huang,Ellen Novoseller,Daniel Seita,Jeffrey Ichnowski,Michael Laskey,Ri of “dual use” satellites that simultaneously provide capacity to both commercial/civilian users and the military. This chapter examines a number of specific aspects of the . principles as they relate to the use of outer space, as well as more recent initiatives aimed at attempting to provide furthe

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Colin Kohler,Robert Platt of “dual use” satellites that simultaneously provide capacity to both commercial/civilian users and the military. This chapter examines a number of specific aspects of the . principles as they relate to the use of outer space, as well as more recent initiatives aimed at attempting to provide furthe

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s paper will first introduce ESA and its constituency, and then it will address the security-specific aspects of its space missions. Threats specific to the different types of missions from the cyberspace will be presented, and possible countermeasures will be analyzed. The motivations that may indu

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Pengzhi Yang,Haowen Liu,Monika Roznere,Alberto Quattrini Lie chapter argues that the pace and nature of these international space partnerships concluded by China and Russia present a strategic and competitive challenge for Europe, the USA, and other allies, including the development of global space governance, as well as market based on transparency, good g

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2511-1256 ing a lively, intimate, forward-looking forum for discussion and debate about the status and future trends of robotics, with emphasis on its potential role to benefit humans..978-3-031-25557-1978-3-031-25555-7Series ISSN 2511-1256 Series E-ISSN 2511-1264

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Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping Through Continual Learningging online data. We extensively evaluate CL-SLAM on three different datasets and demonstrate that it outperforms several baselines inspired by existing continual learning-based visual odometry methods. We make the code of our work publicly available at ..

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Efficiently Learning Single-Arm Fling Motions to Smooth Garmentsency while the execution-time stopping criteria leverage repeated fling actions to increase performance. Compared to baselines, the proposed method significantly accelerates learning. Moreover, with prior experience on similar garments collected through self-supervision, the MAB learning time for a

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