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Consequently, laser range sensing can accurately localize the gear meshing actuator during objective tasking.
In this evaluation, we can showcase several error sources which are characteristic to the different range sensing technologies.
Close range sensing from remotely piloted aircraft systems (RPAS) commonly deliver high volumes of data by providing very-high resolution imagery.
3D range sensing is an important topic in robotics, as it is a component in vital autonomous subsystems such as for collision avoidance, mapping and perception.
For simplicity, the algorithm is implemented in a planar space on our differentially driven mobile robot X1, based on its range sensing and self-localization capabilities.
This consumer-grade range sensing technology is used for markerless tracking on the three-dimensional (3D) coordinate points of object surfaces.
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Some aren't capable of long-range sensing.
A wide-range sensing of 50 ppm to 2% H2 with the robust nanotube sensor was realized.
In particular RPAS are applied to fields that benefit from close-range sensing, such as 3D modelling of cultural heritage and archaeology, environmental sciences, precision forestry and precision agriculture [3 7].
It also presents an approach for generating local occupancy grid maps, using a feed forward NN to interpret sensor readings and a Bayesian update rule to integrate over time-range sensing data.
Through extensive simulations, we systematically study the effect of sampling rates, transmission energy consumption models, communication ranges, and sensing ranges on the lifetime.
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