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Over the years increasingly sophisticated planning algorithms have been developed.
Once the radiotherapy target has been defined, treatment planning algorithms have emerged that can account for many sources of systematic and random errors, including those arising from motion-derived uncertainties during imaging of lung lesions.
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A comparison with well-known path planning algorithms has also been included.
Comparison with well-known path planning algorithms has also been included.
The path planning algorithm has been tested in simulation using the previous control architecture.
A heuristic network planning algorithm has been developed and validated for the prediction of path loss in indoor environments.
The path planning algorithm has been developed based upon the angle guidance fast marching square method, which is able to calculate the optimal path according to vehicle's motion constraints.
An improved space-filling curve (ISFC) tool path planning algorithm has been proposed to exploit the advantage of T-spline as a mathematical representation of free-form surfaces in CAM process, as well as to overcome its disadvantages such as irregular boundaries and holes in the pre-image.
The details regarding the SmartArc planning algorithm have been described by Bzdusek et al. [ 17].
Travel-planning algorithms have become essential software for drivers of electric cars, to help reduce range anxiety.
We show that exploiting historical data about traffic accidents using a stochastic planning algorithm has beneficial effects on solution quality in certain conditions.
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