安全和交互式自治:从形式化方法开始的旅程(主题演讲)

Dorsa Sadigh
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引用次数: 0

摘要

当今社会正迅速向与人类互动和协作的自主系统发展,例如,与驾驶员和行人互动的半自动车辆,与医生合作使用的医疗机器人,或与智能家居中的用户互动的服务机器人。随着自动化系统在我们日常生活中的出现,我们需要设计算法和工具,使我们能够与人进行安全无缝的互动。在这次演讲中,我将通过讨论安全自主系统的一系列观点来开始我为人机系统提供安全的旅程,包括用于合成可证明正确的控制器的形式化方法视角,鲁棒控制方法,以及安全学习和验证方面的最新进展。然后,我将讨论人机系统安全的主要挑战之一,即研究机器人如何在一对一或群体设置中影响人类的行为。这一点通常被忽视,因为我们假设人类就像移动障碍物一样充当外部干扰,或者假设自动化总是能帮助社会,而没有真正考虑人类会受到怎样的影响。我将讨论我们最近在建立人类行为计算模型方面的工作,这些模型来自专家演示和与自主系统交互时的偏好,以及它为安全性和鲁棒性验证带来的挑战。
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Safe and Interactive Autonomy: A Journey Starting from Formal Methods (Keynote)
Todays society is rapidly advancing towards autonomous systems that interact and collaborate with humans, e.g., semiautonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. With the emergence of autonomous systems in our every day lives, we need to design algorithms and tools that enable safe and seamless interactions with people.In this talk, I will start with my journey in providing safety for human-robot systems by discussing a spectrum of views on safe autonomous systems including a formal methods perspective for synthesizing provably correct controllers, a robust control approach, and more recent advances in safe learning and verification. I will then discuss one of the main challenges of safety of human-robot systems, i.e., studying how robots influence humans actions in one-on-one or group settings. This is usually overlooked by assuming humans act as external disturbances just like moving obstacles, or assuming that automation can always help societies without actually considering how humans can be impacted. I will talk about our recent work in building computational models of human behavior from expert demonstrations and preferences in interaction with autonomous systems and challenges it introduces for safety and robustness verification.
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