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I've currently built a quadrotor with standard PID controllers for attitude, angular rates, and position control. I now want to implement obstacle avoidance and path planning using A*. I have a stereo sensor that outputs depth maps, however I am not sure how to use depth maps to translate into the path planner.

Do I have to first use SLAM techniques to create a local map from the depth maps, and then use A* on that local map? Any relevant material is appreciated.

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I would recommend using some sort of discretized local map. For 3D use octomap (https://octomap.github.io/) and 2D a grid map. But honestly, I would try the laziest option, putting each depth reading in octomap form and planning with it to see if a local map is really needed. Remember that you have to represent non-occupied space to use A*. The discretized representation of octomap is well suited for it.

Summing up,

Depth map reading -> To discretized octomap form -> Plan -> Repeat

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  • $\begingroup$ Thank you very much. This helped a lot. Would you mind elaborating on "putting each depth reading in octomap form and planning with it to see if a local map is really needed"? I read the paper but don't quite fully grasp it. $\endgroup$
    – pterodon
    Feb 24, 2019 at 12:07
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    $\begingroup$ A local map, in general, is the mean of sensor readings (a LiDAR for instance), over a period of time to mitigate sensor noise. What I'm suggesting is to not use this approach and instead to transform every reading in an octomap. Because to build a local map would require the vehicle to remain stationary. If this approach does not work, then you would have to rely on a local map. $\endgroup$
    – Akindart
    Feb 24, 2019 at 19:11

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