首页> 外文会议>2011 IEEE 9th Latin American Robotics Symposium and IEEE Colombian Conference on Automatic Control >An autonomous ground explorer utilizing a vision-based approach to indoor navigation
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An autonomous ground explorer utilizing a vision-based approach to indoor navigation

机译:利用基于视觉的方法进行室内导航的自主地面探险者

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We introduce a vision system based approach to autonomous navigation and mapping in an indoor environment. Our goal is to eventually use a common processing system that relies on using airborne and ground vehicles. This paper presents our initial results for a ground vehicle and demonstrates the potential of the vision based system for a solution that combines airborne vehicles with ground vehicles. The Autonomous Ground Explorer (AGE) described here serves as a test vehicle to validate the algorithms that will be integrated into our aerial vehicle that is under development. The ground explorer uses only vision (three basic web cameras augmented with simple laser pointers) to efficiently move within building corridors. It can estimate distance in three directions by evaluating the location of laser points within its fields of vision. The ground explorer navigates hallways and makes directional decisions based on the following processes: tracking the corridor's visual vanishing point, anticipating intersections using odometry and corner edge detection, identifying and classifying intersections based on distance measurements and vanishing points, and completing controlled turns based on a confidence factor in its location on a calculated route within a simplified topological map. Experimental results show the effectiveness of our approach and the promise of our combined ground/aerial system concept.
机译:我们在室内环境中介绍了一种基于视觉系统的自主导航和映射方法。我们的目标是最终使用依赖于使用空中和地面车辆的公共处理系统。本文介绍了地面车辆的初始结果,并展示了基于视觉系统的潜力,用于将空气机与地面车辆结合的解决方案。这里描述的自主地面资源管理器(年龄)用作测试车辆,以验证将集成到正在开发的我们的航空公司中的算法。地面资源管理器仅使用视野(三个基本的Web摄像机,增强了简单的激光指针),以有效地在建筑走廊内移动。它可以通过评估其视野中的激光点的位置来估计三个方向的距离。地面资源管理器导航走廊并根据以下过程进行定向决策:跟踪走廊的视觉消失点,使用内径测量和角落边缘检测,基于距离测量和消失点来识别和分类交叉点,并完成基于a的控制转弯在简化拓扑图中计算的路线上的位置处于其位置的置信因子。实验结果表明了我们的方法的有效性以及我们合并地面/空中系统概念的承诺。

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