Robot obstacle avoidance path planning based on RRT algorithm using MATLAB
Path planning is one of the important tasks in robot navigation, which involves determining the best path for the robot to move in the environment to complete a specific task while avoiding collisions or avoiding obstacles. One of the commonly used path planning algorithms is Rapidly-exploring Random Trees (RRT), which is a search algorithm based on random sampling for searching feasible paths in high-dimensional space. This article will introduce how to use MATLAB to implement robot obstacle avoidance path planning based on the RRT algorithm, and provide the corresponding source code.
First, we need to define the robot's motion model and environment. In this example, we will consider a simplified two-dimensional planar environment where the robot can move in straight lines but cannot pass through obstacles. We assume that the starting position of the robot is (start_x, start_y), the target position is (target_x, target_y), and the position and shape of the obstacles are defined by a set of rectangular areas.
The following is an example of MATLAB code:
% 定义机器人的起始位置和目标位置
start_x = 1;
start_y = 1;
target_x = 10;
target_y