RRT

A simple and extensible Rust library implementing Rapidly-Exploring Random Trees for robot motion planning.

Demo in 2D

The GIF above is generated by examples/rrt2d.rs. It uses a point robot, spherical obstacles, a uniform sampling distribution with 5% goal bias and a straight line steering mechanism. The red path shows the path found by RRT. The green path is after applying shortcutting with rrt::smoothing::fast_shortcutting.

Using RRT for your own robots

The RRT library is designed to be applicable to a wide variety of robots. Therefore, we use generic parameters. To use an RRT you will need to implement and specify the following generics.

• F (num_traits::Float) : the floating point type (implements num_traits::Float)
• N (usize) : the number of dimensions in the state space
• VC (rrt::ValidityChecker) : provides functions to check if points and edges in state space are valid (not in collision)
  • Your implementation should consider the geometry of your robot and the environment
    • If you are planning in joint space for a serial manipulator, this will need to perform forward kinematics for collision checking
• SD (rrt::SamplingDistribution) : provides a function to sample points from the state space
  • For most applications, rrt::GoalBiasedUniformDistribution is sufficient
• ST (rrt::Steering) : provides a function to generate a new point by steering from one point towards the direction of another
  • For applications in which you do not care about robot dynamics, rrt::EuclideanSteering is sufficient
• NN: (rrt::NearestNeighbors) : data structure for efficient nearest neighbors
  • For most applications, rrt::KdTreeNearestNeighbors is sufficient (implemented using kiddo library)