
上QQ阅读APP看书,第一时间看更新
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图1-7 点云降采样算法框图
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图1-9 点云分割算法示意
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图1-10 三个场景下的分割示例
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图1-11 两种算法的点云降采样示例
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图1-12 Scan-to-SubMap匹配过程
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图1-17 三种算法的ROC曲线
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图1-18 场景卫星图及MIM_SLAM算法建立的点云地图
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图1-26 点线特征2实体视觉惯性定位方法示意图
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图1-29 精度实验结果
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图1-30 灵敏度实验结果
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图1-31 鲁棒性实验结果图
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图1-32 相对定位示意图
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图1-33 流形导航示意图
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图1-34 流形导航示意图的记忆机制示意图
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图1-36 运行路线卫星图
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图1-37 有/无记忆机制下的定位成功率对比
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图1-38 每次运行结束后地图节点数
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图1-47 二级融合模块速度对比结果
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图1-48 二级融合模块经纬度和高度对比结果
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图1-64 异构无线传感器网络系统结构
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图2-5 不透明塑料袋包装
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图2-6 纸袋包装
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图2-7 手提包包装
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图2-8 温度变化实验成像图
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图2-45 面向警用的危险目标语义级图像分割
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图2-46 面向警用危险目标的结合图像语义信息的图像实例分割
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图3-9 改进的机械臂模型
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图3-10 运动规划轨迹
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图3-27 Octree障碍模型
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图4-10 GPS路径设置和导航测试图
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图4-19 屏蔽RTK GPS信号时,机器人基于SLAM地图的自主导航情况
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图4-20 RTK GPS信号恢复情况下,机器人利用GPS数据进行导航
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图4-55 小地图界面
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图5-31 稳定裕度等高线
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图5-59 位移云图
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图5-60 应力云图
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图5-70 温升测试
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图6-8 红外人体检测示意图