a similar fashion to Theta*) and intelligent sampling (by biasing sampling towards path vertices, which – after path optimization – are likely to be close to obstacles) A*-RRT and A*-RRT*, a two-phase motion planning method that uses a graph search algorithm to search for an initial feasible path in a low-dimensional space (not considering the complete state space) in a first phase, avoiding hazardous areas and preferring low-risk routes, which is then used to focus the RRT* search in the continuous high-dimensional space in a second phase RRT*FN, RRT* with a fixed number of nodes, which randomly removes a leaf node in the tree in every iteration RRT*-AR, sampling-based alternate routes planning Informed RRT*, improves the convergence speed of RRT* by introducing a heuristic, similar to the way in which A* improves upon Dijkstra's algorithm Real-Time RRT* (RT-RRT*), a variant of RRT* and informed RRT* that uses an online tree rewiring strategy that allows the tree root to move with the agent without discarding previously sampled paths, in order to obtain real-time path-planning in a dynamic environment such as a computer game RRT and RRT, optimization of RRT* for dynamic environments Theta*-RRT, a two-phase motion planning method similar to A*-RRT* that uses a hierarchical combination of any-angle search with RRT motion planning for fast trajectory generation in environments with complex nonholonomic constraints RRT* FND, extension of RRT* for -dynamic environments RRT-GPU, three-dimensional RRT implementation that utilizes hardware acceleration APF-RRT, a combination of RRT planner with Artificial Potential Fields method that simplify the replanning task CERRT, a RRT planner modeling uncertainty, which is reduced exploiting contacts MVRRT*, Minimum violation RRT*, an algorithm that finds the shortest route that minimizes the level of unsafety (the "cost" of the environment rules that have been violated, e.g. traffic laws) RRT-Blossom, RRT planner for highly constrained environments. RRV, efficiently expand the tree around obstacles and through narrow passages, using dominant eigenvectors around tree nodes. RBT, uses simple distance computations in the workspace to expand the tree instead of expensive collision check. TB-RRT, Time-based RRT algorithm for rendezvous planning of two dynamic systems. RRdT*, a RRT*-based planner that uses multiple local trees to actively balances the exploration and exploitation of the space by performing local sampling. See also Any-angle path planning Probabilistic roadmap Space-filling tree Motion planning Randomized algorithm References External links Java visualizer of RRT and RRT* including map editor C++ implementation of RRT using