基于SLAM的扫地机器人控制系统研究

发布时间：2018-05-11 15:57

本文选题：单目视觉SLAM + 三维地图　；参考：《哈尔滨工业大学》2017年硕士论文

【摘要】：吸尘器的发明,改善了人们的劳动条件,提高了人们的清洁效率并降低了了人们的劳动强度,使清洁环境的工作变得简单而有效率。但传统的吸尘器体积大、需要专门人员操作,智能化程度不足。随着科技的不断进步,扫地机器人结合了传统吸尘器与自主移动机器人的优点出现在市场上,并从最初的随机碰撞式扫地机器人逐渐向着路径规划式扫地机器人演变。基于视觉SLAM技术的快速发展,扫地机器人成了视觉SLAM技术从实验室走进市场的突破口之一。但现在市场上的路径规划式智能扫地机器人的价格一直居高不下,而且很多都是国外产品,价格便宜的扫地机器人又不具备足够的智能。为了降低扫地机器人的成本,提高随机碰撞式扫地机器人的智能化程度并对当前流行的视觉SLAM算法进行应用研究,本文对基于SLAM的扫地机器人控制系统进行了研究。根据扫地机器人的使用环境与使用要求,选择并改进了相关算法实现了扫地机器人环境建图功能和路径规划功能。针对LSD-SLAM算法获得的环境地图与路径规划算法所使用环境地图不一致的问题,采用octomap方法和三维投影变换原理实现了地图类型转换。在栅格地图的基础上,针对内螺旋算法容易陷入死区的问题,使用A*算法对其做了改进以实现扫地机器人全覆盖路径规划。为验证算法的实际效果,本文进行了扫地机器人控制系统总体方案设计,说明了实验平台各模块构成及功能,根据功能和使用要求选择了合适的硬件设备,并进行了相关计算,完成了扫地机器人控制系统构建。本文完成了单目摄像头的标定,进行了扫地机器人环境建图实验与路径规划实验。经验证,所采用的LSD-SLAM算法获得的点云图最大相对误差为1.36cm。在栅格边长为14cm的二维栅格地图基础上进行了点到点路径规划实验和全覆盖路径规划实验,点到点路径规划可以使扫地机器人避开障碍物障到达指定位置,全覆盖路径规划所得路径的重复率为2.7%,覆盖率为100%。
[Abstract]:The invention of vacuum cleaner improves people's working conditions, improves people's cleaning efficiency, reduces people's labor intensity, and makes the work of clean environment simple and efficient. However, the traditional vacuum cleaner is large in size and needs special personnel to operate, so the degree of intelligence is insufficient. With the development of science and technology, floor sweeping robot combines the advantages of traditional vacuum cleaner and autonomous mobile robot in the market, and evolves from the initial random impact floor sweeping robot to the path planning floor sweeping robot. Based on the rapid development of visual SLAM technology, floor sweeping robot has become one of the breakthrough points of visual SLAM technology from laboratory to market. However, the price of path-planning intelligent floor sweeping robots on the market has been high all the time, and many of them are foreign products, and the cheap ones do not have enough intelligence. In order to reduce the cost of floor sweeping robot, improve the intelligent degree of random colliding floor sweeping robot, and apply the popular visual SLAM algorithm, this paper studies the control system of floor sweeping robot based on SLAM. According to the use environment and requirements of the floor sweeping robot, the related algorithms are selected and improved to realize the mapping function and path planning function of the floor sweeping robot environment. In order to solve the problem that the environmental map obtained by LSD-SLAM algorithm is inconsistent with the environmental map used by path planning algorithm, the octomap method and the three-dimensional projection transformation principle are used to realize the map type conversion. Based on the raster map, aiming at the problem that the inner spiral algorithm is easy to fall into the dead zone, the A* algorithm is improved to realize the full coverage path planning of the floor sweeping robot. In order to verify the actual effect of the algorithm, this paper designs the overall scheme of the floor sweeping robot control system, explains the composition and function of each module of the experimental platform, selects the appropriate hardware equipment according to the function and usage requirements, and carries out the relevant calculation. The control system of floor sweeping robot is constructed. In this paper, the calibration of monocular camera is completed, and the environmental mapping experiment and path planning experiment of floor sweeping robot are carried out. It is verified that the maximum relative error of the point cloud image obtained by the LSD-SLAM algorithm is 1.36 cm. Point-to-point path planning experiment and full coverage path planning experiment are carried out on the basis of two-dimensional raster map with grid side length 14cm. Point-to-point path planning can enable the robot to avoid obstacles to reach the designated position. The path repetition rate of full coverage path planning is 2. 7%, and the coverage rate is 100%.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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