- 文本
- 历史
从图中可以看出，存在噪声的情况下，里程计模型计算的路径和真实路径偏差较
从图中可以看出，存在噪声的情况下，里程计模型计算的路径和真实路径偏差较大。图中绿色线段表示的是EKF算法融合下的机器人路径，蓝色线段表示UKF算法融合下的机器人路径。两种融合算法得出的机器人运动路径和真实路径比较吻合，从图中可以看出，基于UKF的融合算法得出的路径比基于EKF的融合算法得出的路径更加准确。两种算法具体的定位误差见图34。
0/5000
It can be seen from the figure that in the presence of noise, the path calculated by the odometer model deviates greatly from the real path. The green line in the figure represents the robot path fused by the EKF algorithm, and the blue line represents the robot path fused by the UKF algorithm. The robot motion path obtained by the two fusion algorithms is more consistent with the real path. It can be seen from the figure that the path obtained by the UKF-based fusion algorithm is more accurate than the path obtained by the EKF-based fusion algorithm. The specific positioning errors of the two algorithms are shown in Figure 34.
正在翻译中..
As can be seen from the figure, the path and real path deviation calculated by the odometer model are large in the case of noise. The green segment in the figure represents the robot path under the fusion of the EKF algorithm, and the blue segment represents the robot path under the fusion of the UKF algorithm. The robot motion path and the real path obtained by the two fusion algorithms are more consistent, and it can be seen from the graph that the path based on the fusion algorithm of UKF is more accurate than the path derived from the fusion algorithm based on EKF. The specific positioning error of the two algorithms is shown in Figure 34.
正在翻译中..
It can be seen from the figure that, in the presence of noise, there is a large deviation between the path calculated by odometer model and the real path. In the figure, the green line segment represents the robot path under the fusion of EKF algorithm, and the blue line segment represents the robot path under the fusion of UKF algorithm. The robot motion path obtained by the two fusion algorithms is consistent with the real path. It can be seen from the figure that the path obtained by the fusion algorithm based on UKF is more accurate than that obtained by the fusion algorithm based on EKF. The specific positioning errors of the two algorithms are shown in Figure 34.<br>
正在翻译中..
其它语言
本翻译工具支持: 世界语, 丹麦语, 乌克兰语, 乌兹别克语, 乌尔都语, 亚美尼亚语, 伊博语, 俄语, 保加利亚语, 信德语, 修纳语, 僧伽罗语, 克林贡语, 克罗地亚语, 冰岛语, 加利西亚语, 加泰罗尼亚语, 匈牙利语, 南非祖鲁语, 南非科萨语, 卡纳达语, 卢旺达语, 卢森堡语, 印地语, 印尼巽他语, 印尼爪哇语, 印尼语, 古吉拉特语, 吉尔吉斯语, 哈萨克语, 土库曼语, 土耳其语, 塔吉克语, 塞尔维亚语, 塞索托语, 夏威夷语, 奥利亚语, 威尔士语, 孟加拉语, 宿务语, 尼泊尔语, 巴斯克语, 布尔语(南非荷兰语), 希伯来语, 希腊语, 库尔德语, 弗里西语, 德语, 意大利语, 意第绪语, 拉丁语, 拉脱维亚语, 挪威语, 捷克语, 斯洛伐克语, 斯洛文尼亚语, 斯瓦希里语, 旁遮普语, 日语, 普什图语, 格鲁吉亚语, 毛利语, 法语, 波兰语, 波斯尼亚语, 波斯语, 泰卢固语, 泰米尔语, 泰语, 海地克里奥尔语, 爱尔兰语, 爱沙尼亚语, 瑞典语, 白俄罗斯语, 科西嘉语, 立陶宛语, 简体中文, 索马里语, 繁体中文, 约鲁巴语, 维吾尔语, 缅甸语, 罗马尼亚语, 老挝语, 自动识别, 芬兰语, 苏格兰盖尔语, 苗语, 英语, 荷兰语, 菲律宾语, 萨摩亚语, 葡萄牙语, 蒙古语, 西班牙语, 豪萨语, 越南语, 阿塞拜疆语, 阿姆哈拉语, 阿尔巴尼亚语, 阿拉伯语, 鞑靼语, 韩语, 马其顿语, 马尔加什语, 马拉地语, 马拉雅拉姆语, 马来语, 马耳他语, 高棉语, 齐切瓦语, 等语言的翻译.
