Purposive Vision in Robot Exploration of Three-Dimensional Scenes

任何配备摄像头并在未知的三维环境中工作的机器人都具有两种基本能力，即探索环境和规划一条无碰撞的路径以到达期望的位置。本研究项目的重点是开发具有可证明属性的策略，实时操作，并依赖于可有效计算的定性视觉信息来控制机器人的运动。由于机器人在环境中以连续的方式移动，因此探索和路径规划被建模为连续的动态过程，其中运动规划和视觉感知紧密耦合并同时发生。随着环境障碍的几何约束变得越来越弱，这两个过程之间的联系变得越来越强。在某种程度上的不确定性，这种联系导致了路径规划复杂性的质的飞跃，使得对环境障碍的视觉探索成为必要。为了解决这些问题，研究了环境中已探索部分与未探索部分之间的边界动力学。所开发的策略旨在构造机器人的运动，使该边界的表示简单而定性，可以有效地从定性的视觉信息中导出，其动态演变是可预测的，并可用于进一步指导机器人的运动。这项研究将更好地理解三维运动规划与视觉感知之间的联系，并为诸如到达理想位置、测量未知环境（例如沉船）、识别物体或学习未知物体形状等问题提供主动的探索性策略。

Two abilities fundamental to any robot equipped with a camera and functioning within an unknown, three-dimensional environment are exploring the environment and planning a collision-free path to reach a desired location. The focus of this research project is on the development of strategies that have provable properties, operate in real-time, and rely on efficiently-computable, qualitative visual information to control the motion of the robot. Because the robot moves in the environment in a continuous fashion, exploration and path planning is modeled as continuous, dynamic processes where motion planning and visual sensing are tightly coupled and occur simultaneously. The connection between these two processes becomes stronger as the geometric constraints imposed on the environment's obstacles get weaker. At some level of uncertainty, this connection induces a qualitative jump in the complexity of path planning, making visual exploration of the environment's obstacles necessary. To address these problems, the dynamics of the boundary separating the explored from the unexplored parts of the environment are studied. The strategies developed aim to structure the motion of the robot so that the representation of this boundary is simple and qualitative, can be efficiently derived from qualitative visual information, and its dynamic evolution is predictable and can be used to further guide the motion of the robot. This research should provide a better understanding of the connection between motion planning in three dimensions and visual sensing, and lead to the development of active, exploratory strategies for problems such as reaching a desired location, surveying unknown environments (e.g., a ship wreck),recognizing objects, or learning the shape of an unknown object.