How to combine HectorSLAM and RGB-D camera data to achieve 3D mapping?

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There are many ways to approach this problem. I'll outline the simplest one, but your comment about:

to combine the sensor data before applying SLAM

will probably give you a better result. Or approaching this from a tightly-coupled approach, if that's terminology you're familiar with.

The only way to my knowledge that's fully-open source and relatively plug and play is as follows:

1) Use the 2D laser scanner to build a map. This can be done with Hector like you mention, but also slam toolbox, karto, or gmapping.

2) Look at Octomap. Use the positioning provided by the slam algorithm and odometry to project your points of your depth sensor into the global frame provided by the 2D slam

3) Rejoice!

Obvious asterisks:

• While this is a popular method for junior developers and folks that don't want to actually create a SLAM solution, there are clear downsides.

• If you're working with a 2D laser scanner, then you're throwing out a ton of data that could be used to build a better map and position yourself, and only just using that 3D information to build the global model. Calling this 3D SLAM is a bit of a misnomer, but again, its a popular method.

• To increase fidelity, you may need to continuously post the graph to octomap to update the positioning of individual measurements if they shift around. This is necessary for loop closure and reduction of residual error operations. Hector doesn't do loop closures, so that may not be an issue you have the ability to resolve if you're married to Hector.