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This report summarizes a 2023 workshop on software engineering for robotics, highlighting critical challenges in the field. The workshop identified key issues like the simulation-reality gap, integrating machine learning components, and handling the complexity of heterogeneous robot systems. The report proposes several research directions to address these challenges, including developing improved middlewares, architecture description languages, and human-robot interaction models, along with enhancing simulation ecosystems and quality assurance methods. Finally, it emphasizes the need for updated curricula to train future robotics software engineers. The workshop's goal was to foster collaboration and define a research agenda for the next five years.
Source: https://arxiv.org/pdf/2401.12317
This report summarizes a 2023 workshop on software engineering for robotics, highlighting critical challenges in the field. The workshop identified key issues like the simulation-reality gap, integrating machine learning components, and handling the complexity of heterogeneous robot systems. The report proposes several research directions to address these challenges, including developing improved middlewares, architecture description languages, and human-robot interaction models, along with enhancing simulation ecosystems and quality assurance methods. Finally, it emphasizes the need for updated curricula to train future robotics software engineers. The workshop's goal was to foster collaboration and define a research agenda for the next five years.
Source: https://arxiv.org/pdf/2401.12317