Intelligent escape is an interdisciplinary field that employs artificial
intelligence (AI) techniques to enable robots with the capacity to
intelligently react to potential dangers in dynamic, intricate, and
unpredictable scenarios. As the emphasis on safety becomes increasingly
paramount and advancements in robotic technologies continue to advance, a wide
range of intelligent escape methodologies has been developed in recent years.
This paper presents a comprehensive survey of state-of-the-art research work on
intelligent escape of robotic systems. Four main methods of intelligent escape
are reviewed, including planning-based methodologies, partitioning-based
methodologies, learning-based methodologies, and bio-inspired methodologies.
The strengths and limitations of existing methods are summarized. In addition,
potential applications of intelligent escape are discussed in various domains,
such as search and rescue, evacuation, military security, and healthcare. In an
effort to develop new approaches to intelligent escape, this survey identifies
current research challenges and provides insights into future research trends
in intelligent escape.

智能逃生是一个跨学科领域，利用人工智能（AI）技术使机器人能够智能地应对动态、复杂和不可预测的危险情景。本文对智能逃生的最新研究工作进行了全面调查，综述了四种主要的智能逃生方法，并总结了现有方法的优点和局限性。此外，还讨论了智能逃生在搜救、疏散、军事安全和医疗保健等领域的潜在应用。为了开发智能逃生的新方法，本调查确定了当前的研究挑战，并提供了关于未来研究趋势的见解。