论文标题
体现视觉探索的探索
An Exploration of Embodied Visual Exploration
论文作者
论文摘要
具体的计算机视觉考虑了新型非结构化环境中机器人的感知。具体的视觉探索问题特别重要：机器人如何配备了摄像头范围？尽管到目前为止取得了进展，但与此问题有关的许多基本问题仍未得到答复：（i）代理商探索其环境的意义是什么？ （ii）哪些方法很好地工作，在哪些假设和环境环境下？ （iii）当前的方法在哪里不足，未来的工作可能会在哪里改进？在寻求这些问题的答案时，我们首先提出了现有的视觉探索算法的分类法，并创建了标准框架来对其进行基准测试。然后，我们使用所提出的框架对四个最先进的范式进行了彻底的经验研究，并具有两个逼真的模拟3D环境，一个最先进的探索体系结构和多样化的评估指标。我们的实验结果提供了见解，并提出了新的绩效指标和基准，以供将来的视觉探索工作。代码，模型和数据公开可用：https：//github.com/facebookresearch/exploring_exploration
Embodied computer vision considers perception for robots in novel, unstructured environments. Of particular importance is the embodied visual exploration problem: how might a robot equipped with a camera scope out a new environment? Despite the progress thus far, many basic questions pertinent to this problem remain unanswered: (i) What does it mean for an agent to explore its environment well? (ii) Which methods work well, and under which assumptions and environmental settings? (iii) Where do current approaches fall short, and where might future work seek to improve? Seeking answers to these questions, we first present a taxonomy for existing visual exploration algorithms and create a standard framework for benchmarking them. We then perform a thorough empirical study of the four state-of-the-art paradigms using the proposed framework with two photorealistic simulated 3D environments, a state-of-the-art exploration architecture, and diverse evaluation metrics. Our experimental results offer insights and suggest new performance metrics and baselines for future work in visual exploration. Code, models and data are publicly available: https://github.com/facebookresearch/exploring_exploration
