Purposive Vision in Robot Exploration of Three-Dimensional Scenes

机器人探索三维场景中的目的视觉

• 批准号: 9220782
• 负责人: Charles Dyer
• 金额: $ 33.69万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-04-15 至 1997-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9220782&HistoricalAwards=false
• 关键词: Purposive; Vision; Robot; Exploration; Three

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.

任何装有摄像头的机器人都必须具备的两项基本能力 在一个未知的三维环境中运作 正在探索环境，并计划一条无碰撞的道路， 到达所需的位置。 该研究项目的重点是 发展具有可证明性质的策略， 实时操作，并依赖于高效计算， 定性的视觉信息来控制机器人的运动。 因为机器人在环境中以连续的方式移动， 探索和路径规划被建模为连续的、动态的 运动规划和视觉感知紧密结合的过程 耦合，同时发生。 这两者之间的联系 随着几何约束的施加， 环境的障碍变得越来越弱。在某种程度上， 不确定性，这种联系引起了质的飞跃， 复杂的路径规划，使视觉探索的 环境的障碍是必要的。 为了解决这些问题， 将被探索者与被探索者分开的边界的动态 研究环境中未开发的部分。的战略 开发的目的是结构的机器人的运动，使 这个边界的表示是简单和定性的，可以 有效地从定性视觉信息中获得， 动态演变是可预测的，可用于进一步指导 机器人的运动。 这项研究应该提供一个更好的 了解运动规划之间的联系， 尺寸和视觉感知，并导致发展 积极的，探索性的策略，如达到一个 期望的位置，勘测未知的环境（例如，一艘船 残骸），识别物体，或学习未知物体的形状 object.