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Wilde, N. (author), Alonso-Mora, J. (author)We study the problem of finding statistically distinct plans for stochastic task assignment problems such as online multi-robot pickup and delivery (MRPD) when facing multiple competing objectives. In many real-world settings robot fleets do not only need to fulfil delivery requests, but also have to consider auxiliary objectives such as...journal article 2024
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Spahn, M. (author), Wisse, M. (author), Alonso-Mora, J. (author)Optimization fabrics are a geometric approach to real-time local motion generation, where motions are designed by the composition of several differential equations that exhibit a desired motion behavior. We generalize this framework to dynamic scenarios and nonholonomic robots and prove that fundamental properties can be conserved. We show...journal article 2023
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Liu, Xinjie (author), Peters, L. (author), Alonso-Mora, J. (author)Many autonomous agents, such as intelligent vehicles, are inherently required to interact with one another. Game theory provides a natural mathematical tool for robot motion planning in such interactive settings. However, tractable algorithms for such problems usually rely on a strong assumption, namely that the objectives of all players in...journal article 2023
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Bai, X. (author), Fielbaum, Andres (author), Kronmüller, M. (author), Knödler, L. (author), Alonso-Mora, J. (author)This paper studies the multi-robot task assignment problem in which a fleet of dispersed robots needs to efficiently transport a set of dynamically appearing packages from their initial locations to corresponding destinations within prescribed time-windows. Each robot can carry multiple packages simultaneously within its capacity. Given a...journal article 2023
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Schwarting, Wilko (author), Alonso-Mora, J. (author), Pauli, Liam (author), Karaman, Sertac (author), Rus, Daniela (author)Current state-of-the-art vehicle safety systems, such as assistive braking or automatic lane following, are still only able to help in relatively simple driving situations. We introduce a Parallel Autonomy shared-control framework that produces safe trajectories based on human inputs even in much more complex driving scenarios, such as those...conference paper 2017