diff --git a/src/rrt/2dplane/PlaneStateSpace.hpp b/src/rrt/2dplane/PlaneStateSpace.hpp
index 27c07aa..13aebc8 100644
--- a/src/rrt/2dplane/PlaneStateSpace.hpp
+++ b/src/rrt/2dplane/PlaneStateSpace.hpp
@@ -3,6 +3,12 @@
 #include <Eigen/Dense>
 #include <rrt/StateSpace.hpp>
 
+#include <cmath>
+#include <algorithm>
+#include <iostream>
+
+using namespace std;
+
 namespace RRT {
 
 /**
@@ -18,6 +24,31 @@ class PlaneStateSpace : public StateSpace<POINT_CLASS> {
         return POINT_CLASS(drand48() * width(), drand48() * height());
     }
 
+    /**
+     * Generates a point based on a goal bias and a goal state
+     *
+     * @params goalState - Point that we want to extend towards
+     * @params goalBias - Changes likelihood of choosing a point near goal state
+     * @returns POINT_CLASS - random point based on goal bias and goal state
+     */
+    POINT_CLASS randomBiasState(const POINT_CLASS& goalState, float goalBias) const {
+        // Generates random value based on goalBias
+        float logitX = logit(goalBias / 3 + .67, (float) rand() / RAND_MAX);
+        float logitY = logit(goalBias / 3 + .67, (float) rand() / RAND_MAX);
+        float offsetY = 0;
+        float offsetX = 0;
+
+        // Scale X value based on distance from border
+        offsetX = std::max(goalState.x(), width() - goalState.x()) * logitX;
+
+        // Scale Y value based on distance from border
+        offsetY = std::max(goalState.y(), height() - goalState.y()) * logitY;
+        
+        int randX = goalState.x() + offsetX;
+        int randY = goalState.y() + offsetY;
+        return POINT_CLASS(randX, randY);
+    }
+
     POINT_CLASS intermediateState(const POINT_CLASS& source,
                                   const POINT_CLASS& target,
                                   float stepSize) const {
@@ -41,6 +72,17 @@ class PlaneStateSpace : public StateSpace<POINT_CLASS> {
                pt.y() < height();
     }
 
+    /**
+     * Uses the logit function to generate a random value based on a goal bias
+     *
+     * @params goalBias - increases / decreases distance from 0
+     * @params num - value to be inputted into logit function
+     * @returns float - output of logit function scaled based on goal bias
+     */
+    float logit(const float goalBias, const float num) const{
+        return (1 - goalBias) * log(num/(1 - num));
+    }
+
     float width() const { return _width; }
     float height() const { return _height; }
 
diff --git a/src/rrt/StateSpace.hpp b/src/rrt/StateSpace.hpp
index 1c627d5..e78c5fe 100644
--- a/src/rrt/StateSpace.hpp
+++ b/src/rrt/StateSpace.hpp
@@ -22,6 +22,14 @@ class StateSpace {
      */
     virtual T randomState() const = 0;
 
+    /**
+     * Generates a point within the bounds of the state space
+     * based on the goalBias
+     *
+     * @return A biased state
+     */
+    virtual T randomBiasState(const T& goalState, float goalBias) const = 0;
+
     /**
      * Finds a state in the direction of @target from @source.state().
      * This new state will potentially be added to the tree.  No need to do
diff --git a/src/rrt/Tree.hpp b/src/rrt/Tree.hpp
index f807d42..321e7a1 100644
--- a/src/rrt/Tree.hpp
+++ b/src/rrt/Tree.hpp
@@ -235,9 +235,9 @@ class Tree {
      * This is called at each iteration of the run() method.
      */
     Node<T>* grow() {
-        //  extend towards goal, waypoint, or random state depending on the
-        //  biases
-        //  and a random number
+         // extend towards goal, waypoint, or random state depending on the
+         // biases
+         // and a random number
         float r =
             rand() /
             (float)RAND_MAX;  //  r is between 0 and one since we normalize it
@@ -339,7 +339,6 @@ class Tree {
                 nodes.push_back(node);
                 node = node->parent();
             }
-
             // pass them one-by-one to the callback, reversing the order so
             // that the callback is called with the start point first and the
             // dest point last