1 | initial version |

I figured out it is non-trivial in my application to compute `tf(map, odom_future)`

and `tf(odom_future, base_footprint_future)`

given `amcl_pose`

using the method used in AMCL.

As shown in the AMCL ROS webpage, it has the following tfs:

`tf(map, odom) + tf(odom, base_footprint) = tf(map, base_footprint)`

`tf(map, odom)`

is the drifting effect by the odometer.
`tf(odom, base_footprint)`

is the pose of the robot from the odometer reading.

The pose given by AMCL is `tf(map, base_footprint)`

. In my application, since I am predicting the future, the amcl_pose is in the future. In other words, `tf(map, odom)`

, `tf(odom, base_footprint)`

, `tf(map,base_footprint)`

are in the future, while only `tf(map,base_footprint)`

is given by my motion predictor.

One way to overcome this is to build a motion model to predict future robot pose in the `odom`

frame. I.e. `tf(odom, base_footprint)`

, which is not a trivial task. One could use the velocity motion model, but it might be a naive solution.

2 | No.2 Revision |

I figured out it is non-trivial in my application to compute `tf(map, odom_future)`

and `tf(odom_future, base_footprint_future)`

given `amcl_pose`

using the method used in AMCL.

As shown in the AMCL ROS webpage, it has the following tfs:

`tf(map, odom) + tf(odom, base_footprint) = tf(map, base_footprint)`

`tf(map, odom)`

is the drifting effect by the odometer.
`tf(odom, base_footprint)`

is the pose of the robot from the odometer reading.

The pose given by AMCL is `tf(map, base_footprint)`

. In my application, since I am predicting the future, the ~~amcl_pose ~~`amcl_pose`

is in the future. In other words, `tf(map, odom)`

, `tf(odom, base_footprint)`

, `tf(map,base_footprint)`

are in the future, while only `tf(map,base_footprint)`

is given by my motion predictor.

One way to overcome this is to build a motion model to predict future robot pose in the `odom`

~~frame. I.e. ~~frame, i.e. `tf(odom, base_footprint)`

, which is not a trivial task. One could use the velocity motion model, but it might be a naive ~~solution. ~~

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