Poster: How to Raise a Robot - Beyond Access Control Constraints in Assistive Humanoid Robots

N. Hemken, F. Jacob, Fabian Peller-Konrad, Rainer Kartmann, T. Asfour, H. Hartenstein
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Abstract

Humanoid robots will be able to assist humans in their daily life, in particular due to their versatile action capabilities. However, while these robots need a certain degree of autonomy to learn and explore, they also should respect various constraints, for access control and beyond. We explore incorporating privacy and security constraints (Activity-Centric Access Control and Deep Learning Based Access Control) with robot task planning approaches (classical symbolic planning and end-to-end learning-based planning). We report pre-liminary results on their respective trade-offs and conclude that a hybrid approach will most likely be the method of choice.
海报:如何培养机器人-超越辅助类人机器人的访问控制约束
人形机器人将能够在日常生活中帮助人类,特别是由于它们的多功能动作能力。然而,虽然这些机器人需要一定程度的自主性来学习和探索,但它们也应该尊重各种限制,例如访问控制等。我们探索将隐私和安全约束(以活动为中心的访问控制和基于深度学习的访问控制)与机器人任务规划方法(经典符号规划和端到端基于学习的规划)相结合。我们报告了他们各自权衡的初步结果,并得出结论,混合方法最有可能是选择的方法。
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