There is a growing demand for mobile robots to operate in more variable environments, where guaranteeing safe robot navigation is a priority, in addition to time performance. To achieve this, current solutions for local planning use a specific configuration tuned to the characteristics of the application environment. In this paper, we present an approach for developing quality models that can be used by a self-adaptation framework to adapt the local planner configuration at run-time based on the perceived environment. We contribute a definition of a safety model that predicts the safety of a navigation configuration given the perceived environment. Experiments have been performed in a realistic navigation scenario for a retail application to validate the obtained models and demonstrate their integration in a self-adaptation framework.
翻译:除了时间性能之外,在较易变异的环境中,对移动机器人的操作需求也越来越大,在这种环境中,除了时间性能之外,保障安全的机器人导航是一个优先事项。为了实现这一点,目前当地规划的解决方案使用与应用环境特点相适应的具体配置。在本文件中,我们提出了一个方法,用于开发质量模型,供自适应框架使用,以便根据所感知的环境在运行时调整当地规划师的配置。我们提出了安全模型的定义,根据所觉察到的环境预测导航配置的安全性。在现实的导航假设中进行了实验,用于零售应用,验证获得的模型,并证明这些模型融入了自适应框架。