论文标题
故意探索支持陌生世界的航行
Deliberate Exploration Supports Navigation in Unfamiliar Worlds
论文作者
论文摘要
要在新域中很好地执行任务，必须首先对此有所了解。本文报告了一个机器人控制器，用于通过陌生的室内世界导航。基于空间负担，它将计划与反应性启发式方法相结合。但是，在解决特定目标之前，该系统故意探讨了高级连接性，并在认知空间模型中捕获了这些数据。尽管探索时间有限，但在最终的模型中，计划中的规划速度更快，更好地支持在充满挑战，现实的空间中成功旅行。
To perform tasks well in a new domain, one must first know something about it. This paper reports on a robot controller for navigation through unfamiliar indoor worlds. Based on spatial affordances, it integrates planning with reactive heuristics. Before it addresses specific targets, however, the system deliberately explores for high-level connectivity and captures that data in a cognitive spatial model. Despite limited exploration time, planning in the resultant model is faster and better supports successful travel in a challenging, realistic space.
