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Allowing untrained scientists to safely pilot ROVs: Early collision detection and avoidance using omnidirectional vision

机译:允许未经训练的科学家安全地飞行罗夫:使用全向视野进行早期碰撞检测和避免

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The study of underwater environments involves multiple hazards that can compromise the safety of robots. Underwater missions require a high level of attention from Remotely Operated Vehicle (ROV) operators to avoid damage to the robot. For this reason, there is a growing trend in research to develop systems with new capabilities, such as advanced assisted mapping, spatial awareness and safety, and user immersion. The aim of this work is to devise a system that provides the vehicle with proximity awareness capabilities for navigation in complex environments. By using the advantages of omnidirectional multi-camera systems, a much higher level of spatial awareness can be achieved. This paper presents a visual-based multi-camera system which is able to detect the presence of nearby objects in the environment, to create a local map of points, and to assign collision risk values to this map. The system exploits this information to generate warnings when approaching potentially dangerous obstacles and at the same time creates a collision risk map that provides a proximity awareness representation of the environment.
机译:对水下环境的研究涉及多种可能损害机器人安全性的危险。水下任务需要从远程操作的车辆(ROV)运营商的高度关注,以避免损坏机器人。因此,在开发具有新功能的系统的研究中存在越来越大的趋势,例如高级辅助映射,空间意识和安全性以及用户浸没。这项工作的目的是设计一个系统,该系统提供具有在复杂环境中导航的接近感知能力的近距离感知能力。通过使用全向多摄像机系统的优点,可以实现更高水平的空间意识。本文介绍了一种基于视觉的多摄像机系统,能够检测到环境中附近对象的存在,以创建点的本地地图,并为此映射分配碰撞风险值。该系统利用此信息在接近潜在的危险障碍时产生警告,并且同时创建碰撞风险图,该碰撞风险图提供了环境的接近意识表示。

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