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Autoware-FlowChart.drawio
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Autoware-FlowChart.drawio
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<UserObject label="lidar_driver" tooltip="velodyneのdriverです。VLP16, VLP32, VLS128, Livoxなどなど、たくさん種類があります。" id="T4uXMFoD5u3B1nQVuzlc-7">
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<UserObject label="packets_to_<br>pointcloud" tooltip="velodyneのpacketをpointcloud型に変更する" id="T4uXMFoD5u3B1nQVuzlc-11">
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<UserObject label="crop_box_<br>filter_self" tooltip="自車の領域内にある点群を除去する。" link="https://github.com/autowarefoundation/autoware.universe/blob/main/sensing/pointcloud_preprocessor/docs/crop-box-filter.md" id="T4uXMFoD5u3B1nQVuzlc-13">
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<UserObject label="crop_box_<br>filter_mirror" tooltip="自車のサイドミラーの部分に当たった点群を除去する" link="https://github.com/autowarefoundation/autoware.universe/blob/main/sensing/pointcloud_preprocessor/docs/crop-box-filter.md" id="T4uXMFoD5u3B1nQVuzlc-15">
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<UserObject label="ring_outlier_filter" tooltip="点群のノイズ処理を行う
(同一リングから得られたLiDARの点をクラスタリングし、点群数の少ないクラスタに属する点群はノイズとして除去される)" link="https://github.com/autowarefoundation/autoware.universe/blob/main/sensing/pointcloud_preprocessor/docs/ring-outlier-filter.md" id="T4uXMFoD5u3B1nQVuzlc-16">
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<UserObject label="fix_distortion" tooltip="自車の回転によって生じたLiDAR点群の歪みを補正する。(リンクこれで合ってるっけ?)" link="https://github.com/autowarefoundation/autoware.universe/blob/main/sensing/pointcloud_preprocessor/docs/distortion-corrector.md" id="T4uXMFoD5u3B1nQVuzlc-20">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;fillColor=#e1d5e7;strokeColor=#9673a6;sketch=0;" parent="1" vertex="1">
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<UserObject label="packets_to_<br>pointcloud" tooltip="velodyneのpacketをpointcloud型に変更する" id="T4uXMFoD5u3B1nQVuzlc-22">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;fillColor=#e1d5e7;strokeColor=#9673a6;sketch=0;" parent="1" vertex="1">
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<mxCell id="T4uXMFoD5u3B1nQVuzlc-23" value="<span style="color: rgb(0 , 0 , 0) ; font-family: &#34;helvetica&#34; ; font-size: 11px ; font-style: normal ; font-weight: 400 ; letter-spacing: normal ; text-align: center ; text-indent: 0px ; text-transform: none ; word-spacing: 0px ; background-color: rgb(255 , 255 , 255) ; display: inline ; float: none">*/self_cropped/pointcloud</span>" style="edgeStyle=elbowEdgeStyle;rounded=0;comic=0;jumpStyle=arc;orthogonalLoop=1;jettySize=auto;elbow=vertical;html=1;exitX=0.5;exitY=1;exitDx=0;exitDy=0;entryX=0.5;entryY=0;entryDx=0;entryDy=0;startArrow=none;startFill=0;endArrow=classic;endFill=1;" parent="1" source="T4uXMFoD5u3B1nQVuzlc-24" target="T4uXMFoD5u3B1nQVuzlc-26" edge="1">
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<UserObject label="crop_box_<br>filter_self" tooltip="自車の領域内にある点群を除去する。" link="https://github.com/autowarefoundation/autoware.universe/blob/main/sensing/pointcloud_preprocessor/docs/crop-box-filter.md" id="T4uXMFoD5u3B1nQVuzlc-24">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;fillColor=#e1d5e7;strokeColor=#9673a6;sketch=0;" parent="1" vertex="1">
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<UserObject label="crop_box_<br>filter_mirror" tooltip="自車のサイドミラーの部分に当たった点群を除去する" link="https://github.com/autowarefoundation/autoware.universe/blob/main/sensing/pointcloud_preprocessor/docs/crop-box-filter.md" id="T4uXMFoD5u3B1nQVuzlc-26">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;fillColor=#e1d5e7;strokeColor=#9673a6;sketch=0;" parent="1" vertex="1">
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</UserObject>
<UserObject label="ring_outlier_filter" tooltip="点群のノイズ処理を行う
(同一リングから得られたLiDARの点をクラスタリングし、点群数の少ないクラスタに属する点群はノイズとして除去される)" link="https://github.com/autowarefoundation/autoware.universe/blob/main/sensing/pointcloud_preprocessor/docs/ring-outlier-filter.md" id="T4uXMFoD5u3B1nQVuzlc-27">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;fillColor=#e1d5e7;strokeColor=#9673a6;sketch=0;" parent="1" vertex="1">
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</mxCell>
<UserObject label="concat_filter" tooltip="複数のLiDAR点群をまとめて1つにする" link="https://github.com/autowarefoundation/autoware.universe/blob/main/sensing/pointcloud_preprocessor/docs/concatenate-data.md" id="T4uXMFoD5u3B1nQVuzlc-29">
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<object label="gnss_poser" tooltip="MGRS座標系への変換" link="https://github.com/autowarefoundation/autoware.universe/tree/main/sensing/gnss_poser#gnss_poser" linkTarget="_blank" id="T4uXMFoD5u3B1nQVuzlc-32">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;fillColor=#e1d5e7;strokeColor=#9673a6;sketch=0;" parent="1" vertex="1">
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<object label="gnss_driver" desc="MGRS座標系への変換" tooltip="gnssのdriverです" id="T4uXMFoD5u3B1nQVuzlc-34">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;strokeColor=#9673a6;fillColor=#e1d5e7;sketch=0;" parent="1" vertex="1">
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<UserObject label="imu_driver" tooltip="imuのdriverです" id="T4uXMFoD5u3B1nQVuzlc-35">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;strokeColor=#9673a6;fillColor=#e1d5e7;sketch=0;" parent="1" vertex="1">
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<UserObject label="imu_corrector" tooltip="ヨーレートのバイアス除去とかをするノード" link="https://github.com/autowarefoundation/autoware.universe/tree/main/sensing/imu_corrector#imu_corrector" linkTarget="_blank" id="T4uXMFoD5u3B1nQVuzlc-39">
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<mxCell id="T4uXMFoD5u3B1nQVuzlc-40" value="/sensing/imu/imu_data" style="edgeStyle=elbowEdgeStyle;rounded=0;comic=0;jumpStyle=arc;orthogonalLoop=1;jettySize=auto;elbow=vertical;html=1;startArrow=none;startFill=0;endArrow=classic;endFill=1;entryX=0.5;entryY=0;entryDx=0;entryDy=0;exitX=0.5;exitY=1;exitDx=0;exitDy=0;" parent="1" source="T4uXMFoD5u3B1nQVuzlc-39" target="T4uXMFoD5u3B1nQVuzlc-52" edge="1">
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<UserObject label="voxel_grid_<br>downsample_filter" tooltip="立体格子の点群密度が一様になるように点群を間引く。点群密度が正規化されるため、NDTのロバスト化に一役買っている。" id="T4uXMFoD5u3B1nQVuzlc-42">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;fillColor=#dae8fc;strokeColor=#6c8ebf;sketch=0;" parent="1" vertex="1">
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<mxCell id="T4uXMFoD5u3B1nQVuzlc-43" value="pose_twist_fusion_filter/<br>pose_with_covariance_<br>no_yawbias" style="edgeStyle=orthogonalEdgeStyle;rounded=0;comic=0;jumpStyle=arc;orthogonalLoop=1;jettySize=auto;html=1;exitX=0.656;exitY=0.014;exitDx=0;exitDy=0;entryX=1;entryY=0.5;entryDx=0;entryDy=0;startArrow=none;startFill=0;endArrow=classic;endFill=1;exitPerimeter=0;" parent="1" source="T4uXMFoD5u3B1nQVuzlc-44" target="T4uXMFoD5u3B1nQVuzlc-46" edge="1">
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<UserObject label="ekf_localizer" tooltip="Estimate ego vehicle's position, orientation, and velocity by EKF algorithm." link="https://github.com/autowarefoundation/autoware.universe/tree/main/localization/ekf_localizer#overview" linkTarget="_blank" id="T4uXMFoD5u3B1nQVuzlc-44">
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<UserObject label="ndt_scan_matcher" tooltip="LiDARの点群とpointcloud_mapとのマッチングを行い、自己位置を計算する" link="https://github.com/autowarefoundation/autoware.universe/tree/main/localization/ndt_scan_matcher#ndt_scan_matcher" linkTarget="_blank" id="T4uXMFoD5u3B1nQVuzlc-46">
<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;fillColor=#dae8fc;strokeColor=#6c8ebf;sketch=0;" parent="1" vertex="1">
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<mxCell id="T4uXMFoD5u3B1nQVuzlc-47" value="downsample/pointcloud" style="edgeStyle=orthogonalEdgeStyle;rounded=0;comic=0;jumpStyle=arc;orthogonalLoop=1;jettySize=auto;html=1;startArrow=none;startFill=0;" parent="1" source="T4uXMFoD5u3B1nQVuzlc-48" target="T4uXMFoD5u3B1nQVuzlc-46" edge="1">
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<UserObject label="random_<br>downsample_filter" tooltip="点群数が一定以下になるようにランダムに間引く。基本的にはvoxel grid filterで丁度いいくらい点群数になるように調整してあり、点群数のlimiter的な立ち位置が強い
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<mxCell style="rounded=1;whiteSpace=wrap;html=1;comic=0;fillColor=#dae8fc;strokeColor=#6c8ebf;sketch=0;" parent="1" vertex="1">
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<UserObject label="pose_initializer" tooltip="GNSS / Userからラフな初期位置を受け取り、NDT+モンテカルロ法で正確な自己位置を推定して出力する。NDTとはserviceでやり取りする。" link="https://github.com/autowarefoundation/autoware.universe/blob/main/localization/pose_initializer/docs/pose_initializer.md#pose_initializer" linkTarget="_blank" id="T4uXMFoD5u3B1nQVuzlc-50">
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<UserObject label="gyro_odometer" tooltip="車両速度とimuを統合する。いまは確か、ただ単にvx=vehicle, wz=imuだった気がする。" link="https://github.com/autowarefoundation/autoware.universe/tree/main/localization/gyro_odometer#gyro_odometer" linkTarget="_blank" id="T4uXMFoD5u3B1nQVuzlc-52">
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