How can PointCloud Registration be run deterministically?

### Checklist

- [X] I have searched for [similar issues](https://github.com/isl-org/Open3D/issues).
- [X] For Python issues, I have tested with the [latest development wheel](http://www.open3d.org/docs/latest/getting_started.html#development-version-pip).
- [X] I have checked the [release documentation](http://www.open3d.org/docs/release/) and the [latest documentation](http://www.open3d.org/docs/latest/) (for `master` branch).

### My Question

Hello,

I am running pointcloud registration in two steps. First I get an initial estimate using ransac:

```
distance_threshold = self.voxel_size * 1.5
self.logger.info(":: RANSAC registration on downsampled point clouds.")
self.logger.info(f"Since the downsampling voxel size is {self.voxel_size},")
self.logger.info(f"we use a liberal distance threshold {distance_threshold}.")

source_down, source_fpfh = self.extract_FPFH(source_pcd)
target_down, target_fpfh = self.extract_FPFH(target_pcd)

result = o3d.pipelines.registration.registration_ransac_based_on_feature_matching(
source_down, target_down, source_fpfh, target_fpfh, True,
distance_threshold,
o3d.pipelines.registration.TransformationEstimationPointToPoint(False),
3, [
o3d.pipelines.registration.CorrespondenceCheckerBasedOnEdgeLength(
0.9),
o3d.pipelines.registration.CorrespondenceCheckerBasedOnDistance(
distance_threshold)
], o3d.pipelines.registration.RANSACConvergenceCriteria(
self.ransac_iter, self.conf_prob),
seed=0,
)
```

Then, I refine the estimate using ICP:

```
initial_guess = result.transformation
distance_threshold = self.voxel_size * 0.4
radius_normal = self.voxel_size * 2

# Convergence-Criteria for Vanilla ICP
criteria = o3d.pipelines.registration.ICPConvergenceCriteria(
relative_fitness=0.000001,
relative_rmse=0.000001,
max_iteration=self.icp_iter
)

self.logger.info(":: ICP registration is applied on original point")
self.logger.info(" clouds to refine the alignment. This time we use a strict")
self.logger.info(f" distance threshold {distance_threshold}.")
if self.method == "p2p":
self.logger.info(":: Running ICP with p2p")
reg_p2p = o3d.pipelines.registration.registration_icp(
source_pcd,
target_pcd,
distance_threshold,
initial_guess,
o3d.pipelines.registration.TransformationEstimationPointToPoint(),
o3d.pipelines.registration.ICPConvergenceCriteria(max_iteration=self.icp_iter),
)
elif self.method == "p2plane":
self.logger.info(":: Running ICP with p2plane")
source_pcd.estimate_normals(
o3d.geometry.KDTreeSearchParamHybrid(radius=radius_normal, max_nn=30))
target_pcd.estimate_normals(
o3d.geometry.KDTreeSearchParamHybrid(radius=radius_normal, max_nn=30))
reg_p2p = o3d.pipelines.registration.registration_icp(
source_pcd, target_pcd, distance_threshold,
initial_guess,
o3d.pipelines.registration.TransformationEstimationPointToPlane(),
criteria)
else:
raise ValueError(f"Registration method {self.method} not implemented.")
```

I have seen that in this [#3737 ](https://github.com/isl-org/Open3D/pull/3737) the seed should have been added to the method, but it is not the case.

What do you propose? I would need a deterministic method to align pointclouds.

Thanks!