Reactive high-level behavior synthesis for an Atlas humanoid robot

Spyros Maniatopoulos, Philipp Schillinger, Vitchyr H. Pong, David C. Conner, H. Kress-Gazit
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引用次数: 41

Abstract

In this work, we take a step towards bridging the gap between the theory of formal synthesis and its application to real-world, complex, robotic systems. In particular, we present an end-to-end approach for the automatic generation of code that implements high-level robot behaviors in a verifiably correct manner, including reaction to the possible failures of low-level actions. We start with a description of the system defined a priori. Thus, a non-expert user need only specify a high-level task. We automatically construct a formal specification, in a fragment of Linear Temporal Logic (LTL), that encodes the system's capabilities and constraints, the task, and the desired reaction to low-level failures. We then synthesize a reactive mission plan that is guaranteed to satisfy the formal specification, i.e., achieve the task's goals or correctly react to failures. Lastly, we automatically generate a state machine that instantiates the synthesized symbolic plan in software. We showcase our approach using Team ViGIR's software and Atlas humanoid robot and present lab experiments, thus demonstrating the application of formal synthesis techniques to complex robotic systems. The proposed approach has been implemented and open-sourced as a collection of Robot Operating System (ROS) packages, which are adaptable to other systems.
Atlas类人机器人反应性高级行为综合
在这项工作中,我们朝着弥合形式综合理论与其在现实世界、复杂的机器人系统中的应用之间的差距迈出了一步。特别是,我们提出了一种端到端方法,用于自动生成代码,以可验证的正确方式实现高级机器人行为,包括对低级动作可能失败的反应。我们从先验定义的系统描述开始。因此,非专业用户只需要指定一个高级任务。我们在线性时序逻辑(LTL)的片段中自动构造一个正式的规范,该规范对系统的功能和约束、任务以及对低级故障的期望反应进行编码。然后,我们合成一个保证满足正式规范的反应性任务计划,即实现任务目标或正确地对失败做出反应。最后,我们自动生成一个状态机,在软件中实例化合成的符号计划。我们使用团队ViGIR的软件和Atlas人形机器人展示了我们的方法,并进行了实验室实验,从而展示了形式合成技术在复杂机器人系统中的应用。所提出的方法已被实现并作为机器人操作系统(ROS)包的集合开源,这些包可适用于其他系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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