Navigating spatially varied and dynamic environments is one of the key tasks for autonomous agents. In this paper we present a novel method of navigating a mobile platform with one or multiple 3D-sonar sensors. Moving a mobile platform and subsequently any 3D-sonar sensor on it, will create signature variations over time of the echoed reflections in the sensor readings. An approach is presented to create a predictive model of these signature variations for any motion type. Furthermore, the model is adaptive and works for any position and orientation of one or multiple sonar sensors on a mobile platform. We propose to use this adaptive model and fuse all sensory readings to create a layered control system allowing a mobile platform to perform a set of primitive motions such as collision avoidance, obstacle avoidance, wall following and corridor following behaviours to navigate an environment with dynamically moving objects within it. This paper describes the underlying theoretical base of the entire navigation model and validates it in a simulated environment with results that shows the system is stable and delivers expected behaviour for several tested spatial configurations of one or multiple sonar sensors that can complete an autonomous navigation task.

翻译：在空间变化和动态环境中导航是自主代理的关键任务之一。本文提出了一种利用一个或多个三维声纳传感器对移动平台进行导航的新方法。移动平台及其上的任何三维声纳传感器，会导致传感器读数中回波反射随时间产生特征变化。本文提出了一种方法，可为任意运动类型构建这些特征变化的预测模型。此外，该模型具有自适应性，适用于移动平台上一个或多个声纳传感器的任意位置和朝向。我们建议使用此自适应模型融合所有传感读数，构建分层控制系统，使移动平台能够执行一组基本运动，如碰撞规避、障碍物规避、沿墙行走和走廊跟随行为，以在包含动态移动物体的环境中导航。本文描述了整个导航模型的理论基础，并在模拟环境中进行了验证，结果表明系统稳定，并在多种单个或多个声纳传感器的空间配置下，能够完成自主导航任务并展现出预期行为。