Update README.md

FinalProject/README.md

@@ -227,18 +227,24 @@ In the Scene, there are two blocks which we recognize it as obstacles. In order
 boudning sphere on the two blocks.
 So the goal is to to reach to the desired pose as given the user input.
 
-###sampling based planner Algorithm 
+### Sampling based planner Algorithm 
 
 1)The path planing is implemented by using sampling based planner Algorithm. We set a tree strcuture to store all the intermediate path
 to connect betwwen the starting position and goal position. The tree structure has two trees: T(forward) and T(bacward), which served as
 "bisection method" 
+
 First, we check the whether the UR3 robot would encounter with self-Collision or obstacles-collision.
-2)Then we sample random thetas from random uniform distribution, 
+
+2)Then we sample random thetas from random uniform distribution
+
 3)In order to genearte the one goal pose, we check whether the UR3 robot would encounter with 
 self-Collision(its self joints) or obstacles-collision(bounding spheres on the two blocks).
+
 4)if no collision, add the current position/path to T(forward), and iteratetively found new thetas
 in T(forward), while set the new thetas as the child of previous theta
+
 5)And do the same for T(backward)
+
 6)If theta belongs to both  T(forward) and  T(backward), then we have a complete connected path from starting position to desired goal pose.