From e1337b3b14476ad6c07bc1f6d895baefcdb48707 Mon Sep 17 00:00:00 2001 From: ollama Date: Fri, 13 Nov 2026 12:16:51 +0530 Subject: [PATCH] Fix path planning doc typo and DijkstraPlanner docstring --- PathPlanning/Dijkstra/dijkstra.py | 4 ++-- docs/modules/5_path_planning/path_planning_main.rst | 3 +-- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/PathPlanning/Dijkstra/dijkstra.py b/PathPlanning/Dijkstra/dijkstra.py index f5a4703910..0200f1c810 100644 --- a/PathPlanning/Dijkstra/dijkstra.py +++ b/PathPlanning/Dijkstra/dijkstra.py @@ -16,12 +16,12 @@ class DijkstraPlanner: def __init__(self, ox, oy, resolution, robot_radius): """ - Initialize map for a star planning + Initialize grid map for Dijkstra planning ox: x position list of Obstacles [m] oy: y position list of Obstacles [m] resolution: grid resolution [m] - rr: robot radius[m] + robot_radius: robot radius [m] """ self.min_x = None diff --git a/docs/modules/5_path_planning/path_planning_main.rst b/docs/modules/5_path_planning/path_planning_main.rst index 5132760dc5..d489a50d18 100644 --- a/docs/modules/5_path_planning/path_planning_main.rst +++ b/docs/modules/5_path_planning/path_planning_main.rst @@ -3,8 +3,7 @@ Path Planning ============= -Path planning is the ability of a robot to search feasible and efficient path to the goal. The path has to satisfy some constraints based on the robot’s motion model and obstacle positions, and optimize some objective functions such as time to goal and distance to obstacle. In path planning, dynamic programming based approaches and sampling based approaches are widely used[22]. Fig.5 shows simulation results of potential field path planning and LQRRRT* path planning[27]. - +Path planning is the ability of a robot to search for a feasible and efficient path to the goal. The path has to satisfy some constraints based on the robot's motion model and obstacle positions, and optimize some objective functions such as time to goal and distance to obstacle. In path planning, dynamic programming based approaches and sampling based approaches are widely used[22]. Fig.5 shows simulation results of potential field path planning and LQR-RRT* path planning[27]. .. toctree:: :maxdepth: 2 :caption: Contents