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@@ -2154,7 +2154,7 @@ Static Public Member Functions</h2></td></tr>
<tr class="memdesc:acf07e9b146003000fd39ea09472e0418"><td class="mdescLeft">&#160;</td><td class="mdescRight">Type of parameter Optimizer/PixelVariance , as a string: double . <br /></td></tr>
<tr class="separator:acf07e9b146003000fd39ea09472e0418"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1a6053a3f56ee705dd2d880e9394542d" id="r_a1a6053a3f56ee705dd2d880e9394542d"><td class="memItemLeft" align="right" valign="top">static std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classrtabmap_1_1Parameters.html#a1a6053a3f56ee705dd2d880e9394542d">kOptimizerDisparityVariance</a> ()</td></tr>
<tr class="memdesc:a1a6053a3f56ee705dd2d880e9394542d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Key of parameter Optimizer/DisparityVariance : "Disparity variance used on the disparity axis (u - u_right) of stereo / RGB-D bundle adjustment edges. Applies to all BA-capable backends (g2o, GTSAM, Ceres). Defaults to the same value as PixelVariance for backward compatibility. Set higher (e.g. 2-4) if your depth source is noisier than your feature detector's u/v precision (typical for stereo block matchers / SGM at long range). Set lower (e.g. 0.01-0.1) if your depth source is more accurate than the u/v detector (typical for ToF / LiDAR-fused depth where range is measured directly rather than triangulated). Intuition: the lower the disparity variance, the more the optimizer trusts the depth measurements. Geometric note: wider baseline and/or higher image resolution improve a block matcher's effective disparity precision (larger disparity magnitudes and finer sub-pixel refinement), so wide-baseline high-resolution stereo pairs can usually afford a lower disparity variance (e.g. 0.1-0.5); narrow-baseline low-resolution pairs should keep it higher (e.g. 1-4)." Default value: 1.0 ( double ). <br /></td></tr>
<tr class="memdesc:a1a6053a3f56ee705dd2d880e9394542d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Key of parameter Optimizer/DisparityVariance : "Disparity variance used on the disparity axis (u - u_right) of stereo / RGB-D bundle adjustment edges (g2o, GTSAM, Ceres). Defaults to the same value as PixelVariance for backward compatibility. The lower it is, the more the optimizer trusts the depth. Set higher (e.g. 2-4) if the depth is noisier than the features' u/v precision (stereo block matchers / SGM at long range, narrow-baseline low-resolution stereo). Set lower (e.g. 0.01-0.1) if it is more accurate (ToF / LiDAR-fused depth, measured rather than triangulated), or around 0.1-0.5 for wide-baseline high-resolution stereo." Default value: 1.0 ( double ). <br /></td></tr>
<tr class="separator:a1a6053a3f56ee705dd2d880e9394542d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9b2bf1254c87e79d358dd45a27d92254" id="r_a9b2bf1254c87e79d358dd45a27d92254"><td class="memItemLeft" align="right" valign="top">static double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classrtabmap_1_1Parameters.html#a9b2bf1254c87e79d358dd45a27d92254">defaultOptimizerDisparityVariance</a> ()</td></tr>
<tr class="memdesc:a9b2bf1254c87e79d358dd45a27d92254"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default value of parameter Optimizer/DisparityVariance : 1.0 . <br /></td></tr>
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<tr class="memdesc:a25f8b0caf74b406a8ee38c4bfa6fc83f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Type of parameter Odom/GuessMotion , as a string: bool . <br /></td></tr>
<tr class="separator:a25f8b0caf74b406a8ee38c4bfa6fc83f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa5a167189629eabf46a21ab52b3b24c1" id="r_aa5a167189629eabf46a21ab52b3b24c1"><td class="memItemLeft" align="right" valign="top">static std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classrtabmap_1_1Parameters.html#aa5a167189629eabf46a21ab52b3b24c1">kOdomImuGravity</a> ()</td></tr>
<tr class="memdesc:aa5a167189629eabf46a21ab52b3b24c1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Key of parameter Odom/ImuGravity : uFormat("Gravity magnitude (m/s^2) removed from the IMU linear acceleration (used with \"%s\" &gt; 0). Standard gravity by default. Set it to what the accelerometer reads at rest to compensate for its scale error, or for another gravity than Earth's.", <a class="el" href="classrtabmap_1_1Parameters.html#aabd0b7d996517264f6ce43db1aa6ed05" title="Key of parameter Odom/GuessSmoothingDelay : uFormat(&quot;Guess smoothing delay (s). Estimated velocity is...">kOdomGuessSmoothingDelay()</a>.c_str()) Default value: 9.80665 ( float ). <br /></td></tr>
<tr class="memdesc:aa5a167189629eabf46a21ab52b3b24c1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Key of parameter Odom/ImuGravity : uFormat("Gravity magnitude (m/s^2) removed from the IMU linear acceleration (used with \"%s\" &gt; 0). Standard gravity by default. Set it to what the accelerometer reads at rest to compensate for its scale error, or for another gravity than Earth's. 0: estimated from the IMU while it is still (gyro and accelerometer quiet over 0.5 s), with standard gravity until then: the robot should then be perfectly still for a moment (e.g., at start), and a steady acceleration without rotation would be taken for gravity.", <a class="el" href="classrtabmap_1_1Parameters.html#aabd0b7d996517264f6ce43db1aa6ed05" title="Key of parameter Odom/GuessSmoothingDelay : uFormat(&quot;Guess smoothing delay (s). The velocity is avera...">kOdomGuessSmoothingDelay()</a>.c_str()) Default value: 9.80665 ( float ). <br /></td></tr>
<tr class="separator:aa5a167189629eabf46a21ab52b3b24c1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa8989e225d5b1c560c6900f4cbaf765e" id="r_aa8989e225d5b1c560c6900f4cbaf765e"><td class="memItemLeft" align="right" valign="top">static float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classrtabmap_1_1Parameters.html#aa8989e225d5b1c560c6900f4cbaf765e">defaultOdomImuGravity</a> ()</td></tr>
<tr class="memdesc:aa8989e225d5b1c560c6900f4cbaf765e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default value of parameter Odom/ImuGravity : 9.80665 . <br /></td></tr>
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<tr class="memdesc:ad99f9bae5ced320768203bc0c1f9f972"><td class="mdescLeft">&#160;</td><td class="mdescRight">Type of parameter Odom/ImuGravity , as a string: float . <br /></td></tr>
<tr class="separator:ad99f9bae5ced320768203bc0c1f9f972"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aabd0b7d996517264f6ce43db1aa6ed05" id="r_aabd0b7d996517264f6ce43db1aa6ed05"><td class="memItemLeft" align="right" valign="top">static std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classrtabmap_1_1Parameters.html#aabd0b7d996517264f6ce43db1aa6ed05">kOdomGuessSmoothingDelay</a> ()</td></tr>
<tr class="memdesc:aabd0b7d996517264f6ce43db1aa6ed05"><td class="mdescLeft">&#160;</td><td class="mdescRight">Key of parameter Odom/GuessSmoothingDelay : uFormat("Guess smoothing delay (s). Estimated velocity is averaged based on last transforms up to this maximum delay. This can help to get smoother velocity prediction. Last velocity computed is used directly if \"%s\" is set or the delay is below the odometry rate. With an IMU giving orientation and linear acceleration, a delay &gt; 0 also enables the IMU acceleration: the velocity is then the displacement over this delay corrected by the acceleration measured since, so that it is the velocity at the last frame rather than a delayed average, and the motion guess and lidar deskewing (\"%s\") integrate the acceleration from it. Recommended (~0.5 s) with an IMU. With 0, the IMU only gives the orientation. Without IMU, the average is delayed by half this delay: it can make sense for platforms with inertia (e.g., cars at high speed, where one bad frame would otherwise change the predicted velocity a lot), for high frame rates, or when the velocity is used for lidar deskewing, where its noise would feed back into the next poses.", <a class="el" href="classrtabmap_1_1Parameters.html#a15b57b97754e10867ffb5e8682de5431" title="Key of parameter Odom/FilteringStrategy : &quot;0=No filtering 1=Kalman filtering 2=Particle filtering....">kOdomFilteringStrategy()</a>.c_str(), <a class="el" href="classrtabmap_1_1Parameters.html#a5a45711027dd93b66a34e72c20aa2208" title="Key of parameter Odom/Deskewing : uFormat(&quot;Lidar deskewing. If input lidar has time channel,...">kOdomDeskewing()</a>.c_str()) Default value: 0 ( float ). <br /></td></tr>
<tr class="memdesc:aabd0b7d996517264f6ce43db1aa6ed05"><td class="mdescLeft">&#160;</td><td class="mdescRight">Key of parameter Odom/GuessSmoothingDelay : uFormat("Guess smoothing delay (s). The velocity is averaged over the last transforms up to this delay, for a smoother velocity prediction. The last velocity is used directly if \"%s\" is set or the delay is below the odometry rate. With an IMU giving orientation and linear acceleration, a delay &gt; 0 also enables the IMU acceleration: the velocity is the displacement over this delay corrected by the acceleration measured since, so it is not delayed, and the motion guess and lidar deskewing (\"%s\") integrate the acceleration from it (~0.5 s recommended). With 0, the IMU only gives the orientation. Without IMU, the average is delayed by half this delay: useful for platforms with inertia, high frame rates, or lidar deskewing, where the velocity noise would feed back into the next poses.", <a class="el" href="classrtabmap_1_1Parameters.html#a15b57b97754e10867ffb5e8682de5431" title="Key of parameter Odom/FilteringStrategy : &quot;0=No filtering 1=Kalman filtering 2=Particle filtering....">kOdomFilteringStrategy()</a>.c_str(), <a class="el" href="classrtabmap_1_1Parameters.html#a5a45711027dd93b66a34e72c20aa2208" title="Key of parameter Odom/Deskewing : uFormat(&quot;Lidar deskewing. If input lidar has time channel,...">kOdomDeskewing()</a>.c_str()) Default value: 0 ( float ). <br /></td></tr>
<tr class="separator:aabd0b7d996517264f6ce43db1aa6ed05"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab92e1ac2b4bcdcc6551533aaf19aa4e2" id="r_ab92e1ac2b4bcdcc6551533aaf19aa4e2"><td class="memItemLeft" align="right" valign="top">static float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classrtabmap_1_1Parameters.html#ab92e1ac2b4bcdcc6551533aaf19aa4e2">defaultOdomGuessSmoothingDelay</a> ()</td></tr>
<tr class="memdesc:ab92e1ac2b4bcdcc6551533aaf19aa4e2"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default value of parameter Odom/GuessSmoothingDelay : 0 . <br /></td></tr>
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<tr class="memdesc:aa4fae465d9dbe30d6dc967021db3ea5a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Type of parameter Odom/AlignWithGround , as a string: bool . <br /></td></tr>
<tr class="separator:aa4fae465d9dbe30d6dc967021db3ea5a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5a45711027dd93b66a34e72c20aa2208" id="r_a5a45711027dd93b66a34e72c20aa2208"><td class="memItemLeft" align="right" valign="top">static std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classrtabmap_1_1Parameters.html#a5a45711027dd93b66a34e72c20aa2208">kOdomDeskewing</a> ()</td></tr>
<tr class="memdesc:a5a45711027dd93b66a34e72c20aa2208"><td class="mdescLeft">&#160;</td><td class="mdescRight">Key of parameter Odom/Deskewing : uFormat("Lidar deskewing. If input lidar has time channel, it will be deskewed. With an IMU, the pose of every point is predicted from the previous frame: orientation from the IMU, translation from the velocity (with the IMU acceleration if \"%s\" &gt; 0). Without IMU, with a constant motion model (or the guess if provided).", <a class="el" href="classrtabmap_1_1Parameters.html#aabd0b7d996517264f6ce43db1aa6ed05" title="Key of parameter Odom/GuessSmoothingDelay : uFormat(&quot;Guess smoothing delay (s). Estimated velocity is...">kOdomGuessSmoothingDelay()</a>.c_str()) Default value: true ( bool ). <br /></td></tr>
<tr class="memdesc:a5a45711027dd93b66a34e72c20aa2208"><td class="mdescLeft">&#160;</td><td class="mdescRight">Key of parameter Odom/Deskewing : uFormat("Lidar deskewing. If input lidar has time channel, it will be deskewed. With an IMU, the pose of every point is predicted from the previous frame: orientation from the IMU, translation from the velocity (with the IMU acceleration if \"%s\" &gt; 0). Without IMU, with a constant motion model (or the guess if provided).", <a class="el" href="classrtabmap_1_1Parameters.html#aabd0b7d996517264f6ce43db1aa6ed05" title="Key of parameter Odom/GuessSmoothingDelay : uFormat(&quot;Guess smoothing delay (s). The velocity is avera...">kOdomGuessSmoothingDelay()</a>.c_str()) Default value: true ( bool ). <br /></td></tr>
<tr class="separator:a5a45711027dd93b66a34e72c20aa2208"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3a8263972a698faa1da37e4f2007a8d3" id="r_a3a8263972a698faa1da37e4f2007a8d3"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classrtabmap_1_1Parameters.html#a3a8263972a698faa1da37e4f2007a8d3">defaultOdomDeskewing</a> ()</td></tr>
<tr class="memdesc:a3a8263972a698faa1da37e4f2007a8d3"><td class="mdescLeft">&#160;</td><td class="mdescRight">Default value of parameter Odom/Deskewing : true . <br /></td></tr>
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<p>Key of parameter Optimizer/DisparityVariance : "Disparity variance used on the disparity axis (u - u_right) of stereo / RGB-D bundle adjustment edges. Applies to all BA-capable backends (g2o, GTSAM, Ceres). Defaults to the same value as PixelVariance for backward compatibility. Set higher (e.g. 2-4) if your depth source is noisier than your feature detector's u/v precision (typical for stereo block matchers / SGM at long range). Set lower (e.g. 0.01-0.1) if your depth source is more accurate than the u/v detector (typical for ToF / LiDAR-fused depth where range is measured directly rather than triangulated). Intuition: the lower the disparity variance, the more the optimizer trusts the depth measurements. Geometric note: wider baseline and/or higher image resolution improve a block matcher's effective disparity precision (larger disparity magnitudes and finer sub-pixel refinement), so wide-baseline high-resolution stereo pairs can usually afford a lower disparity variance (e.g. 0.1-0.5); narrow-baseline low-resolution pairs should keep it higher (e.g. 1-4)." Default value: 1.0 ( double ). </p>
<p>Key of parameter Optimizer/DisparityVariance : "Disparity variance used on the disparity axis (u - u_right) of stereo / RGB-D bundle adjustment edges (g2o, GTSAM, Ceres). Defaults to the same value as PixelVariance for backward compatibility. The lower it is, the more the optimizer trusts the depth. Set higher (e.g. 2-4) if the depth is noisier than the features' u/v precision (stereo block matchers / SGM at long range, narrow-baseline low-resolution stereo). Set lower (e.g. 0.01-0.1) if it is more accurate (ToF / LiDAR-fused depth, measured rather than triangulated), or around 0.1-0.5 for wide-baseline high-resolution stereo." Default value: 1.0 ( double ). </p>
<p class="definition">Definition at line <a class="el" href="Parameters_8h_source.html#l00492">492</a> of file <a class="el" href="Parameters_8h_source.html">Parameters.h</a>.</p>
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<p>Key of parameter Odom/ImuGravity : uFormat("Gravity magnitude (m/s^2) removed from the IMU linear acceleration (used with \"%s\" &gt; 0). Standard gravity by default. Set it to what the accelerometer reads at rest to compensate for its scale error, or for another gravity than Earth's.", <a class="el" href="classrtabmap_1_1Parameters.html#aabd0b7d996517264f6ce43db1aa6ed05" title="Key of parameter Odom/GuessSmoothingDelay : uFormat(&quot;Guess smoothing delay (s). Estimated velocity is...">kOdomGuessSmoothingDelay()</a>.c_str()) Default value: 9.80665 ( float ). </p>
<p>Key of parameter Odom/ImuGravity : uFormat("Gravity magnitude (m/s^2) removed from the IMU linear acceleration (used with \"%s\" &gt; 0). Standard gravity by default. Set it to what the accelerometer reads at rest to compensate for its scale error, or for another gravity than Earth's. 0: estimated from the IMU while it is still (gyro and accelerometer quiet over 0.5 s), with standard gravity until then: the robot should then be perfectly still for a moment (e.g., at start), and a steady acceleration without rotation would be taken for gravity.", <a class="el" href="classrtabmap_1_1Parameters.html#aabd0b7d996517264f6ce43db1aa6ed05" title="Key of parameter Odom/GuessSmoothingDelay : uFormat(&quot;Guess smoothing delay (s). The velocity is avera...">kOdomGuessSmoothingDelay()</a>.c_str()) Default value: 9.80665 ( float ). </p>
<p class="definition">Definition at line <a class="el" href="Parameters_8h_source.html#l00515">515</a> of file <a class="el" href="Parameters_8h_source.html">Parameters.h</a>.</p>
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<p>Key of parameter Odom/GuessSmoothingDelay : uFormat("Guess smoothing delay (s). Estimated velocity is averaged based on last transforms up to this maximum delay. This can help to get smoother velocity prediction. Last velocity computed is used directly if \"%s\" is set or the delay is below the odometry rate. With an IMU giving orientation and linear acceleration, a delay &gt; 0 also enables the IMU acceleration: the velocity is then the displacement over this delay corrected by the acceleration measured since, so that it is the velocity at the last frame rather than a delayed average, and the motion guess and lidar deskewing (\"%s\") integrate the acceleration from it. Recommended (~0.5 s) with an IMU. With 0, the IMU only gives the orientation. Without IMU, the average is delayed by half this delay: it can make sense for platforms with inertia (e.g., cars at high speed, where one bad frame would otherwise change the predicted velocity a lot), for high frame rates, or when the velocity is used for lidar deskewing, where its noise would feed back into the next poses.", <a class="el" href="classrtabmap_1_1Parameters.html#a15b57b97754e10867ffb5e8682de5431" title="Key of parameter Odom/FilteringStrategy : &quot;0=No filtering 1=Kalman filtering 2=Particle filtering....">kOdomFilteringStrategy()</a>.c_str(), <a class="el" href="classrtabmap_1_1Parameters.html#a5a45711027dd93b66a34e72c20aa2208" title="Key of parameter Odom/Deskewing : uFormat(&quot;Lidar deskewing. If input lidar has time channel,...">kOdomDeskewing()</a>.c_str()) Default value: 0 ( float ). </p>
<p>Key of parameter Odom/GuessSmoothingDelay : uFormat("Guess smoothing delay (s). The velocity is averaged over the last transforms up to this delay, for a smoother velocity prediction. The last velocity is used directly if \"%s\" is set or the delay is below the odometry rate. With an IMU giving orientation and linear acceleration, a delay &gt; 0 also enables the IMU acceleration: the velocity is the displacement over this delay corrected by the acceleration measured since, so it is not delayed, and the motion guess and lidar deskewing (\"%s\") integrate the acceleration from it (~0.5 s recommended). With 0, the IMU only gives the orientation. Without IMU, the average is delayed by half this delay: useful for platforms with inertia, high frame rates, or lidar deskewing, where the velocity noise would feed back into the next poses.", <a class="el" href="classrtabmap_1_1Parameters.html#a15b57b97754e10867ffb5e8682de5431" title="Key of parameter Odom/FilteringStrategy : &quot;0=No filtering 1=Kalman filtering 2=Particle filtering....">kOdomFilteringStrategy()</a>.c_str(), <a class="el" href="classrtabmap_1_1Parameters.html#a5a45711027dd93b66a34e72c20aa2208" title="Key of parameter Odom/Deskewing : uFormat(&quot;Lidar deskewing. If input lidar has time channel,...">kOdomDeskewing()</a>.c_str()) Default value: 0 ( float ). </p>
<p class="definition">Definition at line <a class="el" href="Parameters_8h_source.html#l00516">516</a> of file <a class="el" href="Parameters_8h_source.html">Parameters.h</a>.</p>
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<p>Key of parameter Odom/Deskewing : uFormat("Lidar deskewing. If input lidar has time channel, it will be deskewed. With an IMU, the pose of every point is predicted from the previous frame: orientation from the IMU, translation from the velocity (with the IMU acceleration if \"%s\" &gt; 0). Without IMU, with a constant motion model (or the guess if provided).", <a class="el" href="classrtabmap_1_1Parameters.html#aabd0b7d996517264f6ce43db1aa6ed05" title="Key of parameter Odom/GuessSmoothingDelay : uFormat(&quot;Guess smoothing delay (s). Estimated velocity is...">kOdomGuessSmoothingDelay()</a>.c_str()) Default value: true ( bool ). </p>
<p>Key of parameter Odom/Deskewing : uFormat("Lidar deskewing. If input lidar has time channel, it will be deskewed. With an IMU, the pose of every point is predicted from the previous frame: orientation from the IMU, translation from the velocity (with the IMU acceleration if \"%s\" &gt; 0). Without IMU, with a constant motion model (or the guess if provided).", <a class="el" href="classrtabmap_1_1Parameters.html#aabd0b7d996517264f6ce43db1aa6ed05" title="Key of parameter Odom/GuessSmoothingDelay : uFormat(&quot;Guess smoothing delay (s). The velocity is avera...">kOdomGuessSmoothingDelay()</a>.c_str()) Default value: true ( bool ). </p>
<p class="definition">Definition at line <a class="el" href="Parameters_8h_source.html#l00522">522</a> of file <a class="el" href="Parameters_8h_source.html">Parameters.h</a>.</p>