Mapping

3D environment modeling

In order for robots to navigate and interact more like humans in complex environments, manipulating objects, reacting to dynamic events and coping with changes, they need to have a representation or map of the environment, which can be used as input for autonomous operation.

3D imaging and analysis have a clear advantage over traditional 2D vision for such applications, because the 3D data eases and enhances the detection and positioning of scene objects and structure. This interpretation allows the developed robots to be able to track their position, identify scene elements and adjust their actions in relation to the environment.

Often also a range of multiple sensors are necessary to provide the information required for operation planning and execution. Fusion of sensor data from different sensors then become essential to ensure robust and reliable recognition of environmental shapes, features and properties, important for robust 3D mapping of the scene. To utilize this information, carefully tuned signal processing algorithms and good knowledge of the sensors physical characteristics (strengths and weaknesses) are required.

 
 
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