mrpt_path_planning

Path planning and navigation algorithms for robots/vehicles moving on planar environments. This library builds upon mrpt-nav and the theory behind PTGs to generate libraries of “motion primitives” for vehicles with arbitrary shape and realistic kinematics and dynamics.

The planner optimizes SE(2) path cost (position + heading), not R(2) path length. For vehicles that rotate, arriving at a goal with the correct heading is part of the optimal solution — paths that are longer in Euclidean distance but better-aligned may genuinely have lower cost. See TPS_Astar.h for details on the cost model.

Status on ROS build farm

Distro	Build dev	Build releases	Stable version
ROS 2 Humble (u22.04)
ROS 2 Jazzy @ u24.04
ROS 2 Kilted @ u24.04
ROS 2 Lyrical (u26.04)
ROS 2 Rolling (u26.04)

EOL Distro	Last version
ROS 1 Noetic (u20.04)
ROS 2 Iron (u22.04)

Build requisites

• MRPT (>=2.12.0)
• mvsim (optional to run the live control simulator).

In Ubuntu 22.04 or newer, installed it with:

sudo apt install libmrpt-dev

For older versions of Ubuntu:

# MRPT from this PPA (or build from sources if preferred, or from ROS package `mrpt2`):
sudo add-apt-repository ppa:joseluisblancoc/mrpt
sudo apt update
sudo apt install libmrpt-dev

Use in your code

From your CMake script:

find_package(mrpt_path_planning REQUIRED)
target_link_libraries(YOUR_TARGET mpp::mrpt_path_planning)

Demo runs

path-planner-cli

Dump default planner parameters to a YAML file for inspection or customization:

build/bin/path-planner-cli --write-planner-parameters my-planner-params.yaml

Plan a path for a holonomic robot with an SE(2) goal pose (x y heading_deg), using a pre-built obstacle point cloud and an obstacle-proximity cost map:

build/bin/path-planner-cli \
  -s "[0.5 0 0]" \
  -g "[4 2.5 45]" \
  -c share/ptgs_holonomic_robot.ini \
  --obstacles share/obstacles_01.txt \
  --planner-parameters share/mvsim-demo-astar-planner-params.yaml \
  --costmap-obstacles share/costmap-obstacles.yaml

Plan a path with an R(2) goal (position only, heading-agnostic), printing the edge details of the found path and saving the interpolated trajectory to a CSV:

build/bin/path-planner-cli \
  -s "[0.5 0 0]" \
  -g "[4 2.5]" \
  -c share/ptgs_holonomic_robot.ini \
  --obstacles share/obstacles_01.txt \
  --planner-parameters share/mvsim-demo-astar-planner-params.yaml \
  --print-path-edges \
  --save-interpolated-path path.csv

Plan a path for an Ackermann (car-like) vehicle, show the full explored search tree, and animate the result. Note the goal is given as a position [x y] (R², heading-agnostic): with arc-based PTGs, arriving at a precise heading AND position simultaneously is very constrained, so position-only goals are the natural choice

File truncated at 100 lines see the full file