Finding an object of a specific class in an unseen environment remains an unsolved navigation problem. Hence, we propose a hierarchical learning-based method for object navigation. The top-level is capable of high-level planning, and building a memory on a floorplan-level (e.g., which room makes the most sense for the agent to visit next, where has the agent already been?). While the lower-level is tasked with efficiently navigating between rooms and looking for objects in them. Instructions can be provided to the agent using a simple synthetic language. The top-level intelligently enhances the instructions in order to make the overall task more tractable. Language grounding, mapping instructions to visual observations, is performed by utilizing an additional separate supervised trained goal assessment module. We demonstrate the effectiveness of our method on a dynamic configurable domestic environment.
翻译:在不可见的环境中查找某个特定类的物体仍然是一个尚未解决的导航问题。 因此, 我们提议了一种基于等级学习的物体导航方法。 顶层能够进行高层规划, 并在下层平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面平面( 例如, 下层平面是下层平面, 代理已经去过了? ) 虽然下层平面平面平面负责在各会议室之间有效航行, 并查找其中的物体。 可以使用简单的合成语言向代理提供指示。 顶层平面平面平面平面平面平面平面平面平面平面平面平面平面,对视觉观测指示则使用另外的、有监督的、经过训练的目标评估模块。 我们展示了我们的方法在动态可配置的国内环境中的有效性。