Rapid development of artificial intelligence motivates researchers to expand the capabilities of intelligent and autonomous robots. In many robotic applications, robots are required to make planning decisions based on perceptual information to achieve diverse goals in an efficient and effective way. The planning problem has been investigated in active robot vision, in which a robot analyzes its environment and its own state in order to move sensors to obtain more useful information under certain constraints. View planning, which aims to find the best view sequence for a sensor, is one of the most challenging issues in active robot vision. The quality and efficiency of view planning are critical for many robot systems and are influenced by the nature of their tasks, hardware conditions, scanning states, and planning strategies. In this paper, we first summarize some basic concepts of active robot vision, and then review representative work on systems, algorithms and applications from four perspectives: object reconstruction, scene reconstruction, object recognition, and pose estimation. Finally, some potential directions are outlined for future work.

中文翻译：

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机器人主动视觉中的视图规划：系统，算法和应用程序概览

人工智能的飞速发展促使研究人员扩展智能和自主机器人的功能。在许多机器人应用中，需要机器人根据感知信息做出计划决策，以有效地实现各种目标。已经在主动机器人视觉中研究了规划问题，其中机器人分析其环境和自身状态，以便在某些约束下移动传感器以获得更多有用的信息。旨在为传感器找到最佳视图顺序的视图规划是主动机器人视觉中最具挑战性的问题之一。视图规划的质量和效率对于许多机器人系统至关重要，并且受其任务的性质，硬件条件，扫描状态和规划策略的影响。在本文中，我们首先总结主动式机器人视觉的一些基本概念，然后从四个角度回顾有关系统，算法和应用程序的代表性工作：对象重建，场景重建，对象识别和姿势估计。最后，为将来的工作概述了一些潜在的方向。