OctoMap is an efficient probabilistic 3D mapping framework based on Octrees. This is a python-based implementation of the OctoMap described in:
Hornung, Armin, et al. "OctoMap: An efficient probabilistic 3D mapping framework based on octrees." Autonomous robots 34.3 (2013): 189-206.
In this repository, we provide a basic implementation of OctoMap and a visualization tool and a path plan algorithm (RRT) working with OctoMap.
There are many parameters in the
Config.py, but you should consider only some of them at the most time.
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TREE_CENTER: Indicates an area that can be represented by an octree centered on this point. When the insertion point exceeds this area, the error "Point is not contained in voxel." will be prompted
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SENSOR_TH: The distance measurement of the VL53L1X series laser sensor used by the Multi-ranger deck in this project is accurate within 400cm. This value is determined by the configuration of the selected sensor
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WIDTH: The width of the experimental scene, determined by the area supported by the light-house in this project. When the insertion point is larger than this range, the point is shrunk to the boundary of the experimental scene
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Offset: Place Crazyflie at the center point of the light-house area, and get the coordinates of the corresponding point. When doing visualization processing, you need to add an offset to convert all of them to points in the first quadrant (the initialization values of the visualization coordinate voxels are all positive values)
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URI: Change the URI variable to your Crazyflie configuration.
pip install will be provided soon.