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The Transition-based RRT (T-RRT) algorithm enables to solve motion planning problems involving configuration spaces over which cost functions are defined, or cost spaces for short. T-RRT has been successfully applied to diverse problems in robotics and structural biology. In this paper, we aim at enhancing T-RRT to solve ever more difficult problems involving larger and more complex cost spaces. We...
Finding paths in high-dimensional spaces becomes difficult when we wish to optimize the cost of a path in addition to obeying feasibility constraints. Recently the T-RRT algorithm was presented as a method to plan in high-dimensional cost-spaces and it was shown to perform well across a variety of problems. However, since the T-RRT relies solely on sampling to explore the space, it has difficulty...
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