diff --git a/rb_ws/src/buggy/scripts/auton/path_planner.py b/rb_ws/src/buggy/scripts/auton/path_planner.py
new file mode 100755
index 00000000..5dabef71
--- /dev/null
+++ b/rb_ws/src/buggy/scripts/auton/path_planner.py
@@ -0,0 +1,136 @@
+import numpy as np
+
+import rospy
+from sensor_msgs.msg import NavSatFix
+from std_msgs.msg import Float64
+from geometry_msgs.msg import Pose as ROSPose
+from pose import Pose
+
+from occupancy_grid.grid_manager import OccupancyGrid
+from path_projection import Projector
+from trajectory import Trajectory
+from world import World
+import copy
+
+
+LOOKAHEAD_TIME = 2.0 #s
+RESOLUTION = 30 #samples/s
+PASSING_OFFSET = 2 #m
+# in meters, the number of meters behind NAND before we start morphing the trajectory
+REAR_MARGIN = 10
+
+# in meters, the number of meters in front of NAND, 
+# before the morphed trajectory rejoins the nominal trajectory
+# WARNING: set this value to be greater than 10m/s * lookahead time (10 m/s is the upper limit
+# of NAND speed) Failure to do so can result violent u-turns in the new trajectory.
+
+FRONT_MARGIN = 30
+
+class PathPlanner():
+    def __init__(self, nominal_traj) -> None:
+        self.occupancy_grid = OccupancyGrid()
+
+        # TODO: update with NAND wheelbase
+        self.path_projector = Projector(1.3)
+
+        self.debug_passing_traj_publisher = rospy.Publisher(
+            "/auton/debug/passing_traj", NavSatFix, queue_size=1000
+        )
+
+        self.debug_splice_pt_publisher = rospy.Publisher(
+            "/auton/debug/splice_pts", NavSatFix, queue_size=1000
+        )
+
+
+        self.debug_grid_cost_publisher = rospy.Publisher(
+            "/auton/debug/grid_cost", Float64, queue_size=0
+        )
+        self.last_cmd = 0
+        self.nominal_traj = nominal_traj
+
+        # TODO: estimate this value based on the curvature of NAND's recent positions
+        self.other_steering_angle = 0 
+
+    def compute_traj(
+        self,
+        other_pose: Pose, #Currently NAND's location -- To be Changed
+        other_speed: float):
+
+        # draw trajectory, such that the section of the
+        # trajectory near NAND is replace by a new segment:
+
+        # 1. the global path, at 10m behind NAND
+        # 2. NAND's projected locations, where each location is 
+        # shifted to the left along the normal of the trajectory vector
+
+        other_idx = self.nominal_traj.get_closest_index_on_path(
+            other_pose.x, 
+            other_pose.y)
+        #other is just NAND, for general purposes consider it other
+
+        new_segment_start_idx = self.nominal_traj.get_index_from_distance(
+                self.nominal_traj.get_distance_from_index(other_idx) - 10
+            ) #Where new path index starts, CONSTANT delta from NAND
+        
+        new_segment_end_idx = self.nominal_traj.get_index_from_distance(
+                self.nominal_traj.get_distance_from_index(other_idx) + 30
+            )
+        
+        # project other buggy path
+        # TODO: put other buggy command
+        other_future_poses = self.path_projector.project(
+            other_pose,
+            self.other_steering_angle, 
+            other_speed, 
+            LOOKAHEAD_TIME, 
+            RESOLUTION)
+
+        other_future_poses_idxs = np.empty((len(other_future_poses), ))
+
+        # TODO: optimize this lookup -- how tho
+        for i in range(len(other_future_poses)):
+            other_future_poses_idxs[i] = self.nominal_traj.get_closest_index_on_path(
+                    other_future_poses[i][0],
+                    other_future_poses[i][1],
+                    start_index=other_idx)
+            
+        future_pose_unit_normal = self.nominal_traj.get_unit_normal_by_index(
+            other_future_poses_idxs
+        )
+
+        # the first passing target is 10 meters backward from NAND's position
+        passing_targets = np.array(
+            [self.nominal_traj.get_position_by_index(new_segment_start_idx)])
+        
+        passing_targets = np.vstack((passing_targets, 
+            other_future_poses + PASSING_OFFSET * future_pose_unit_normal))
+        
+        pre_slice = self.nominal_traj.positions[:int(new_segment_start_idx), :]
+        post_slice = self.nominal_traj.positions[int(new_segment_end_idx):, :]
+        new_path = np.vstack((pre_slice, passing_targets, post_slice))
+
+        # publish passing targets for debugging
+        for i in range(len(passing_targets)):
+            reference_navsat = NavSatFix()
+            ref_gps = World.world_to_gps(passing_targets[i, 0], passing_targets[i, 1])
+            reference_navsat.latitude = ref_gps[0]
+            reference_navsat.longitude = ref_gps[1]
+            self.debug_passing_traj_publisher.publish(reference_navsat)
+
+        # for debugging:
+        # publish the first and last point of the part of the original trajectory 
+        # that got spliced out
+        reference_navsat = NavSatFix()
+        ref_gps = World.world_to_gps(*self.nominal_traj.get_position_by_index(int(new_segment_start_idx)))
+        reference_navsat.latitude = ref_gps[0]
+        reference_navsat.longitude = ref_gps[1]
+        self.debug_splice_pt_publisher.publish(reference_navsat)
+
+        ref_gps = World.world_to_gps(*self.nominal_traj.get_position_by_index(int(new_segment_end_idx)))
+        reference_navsat.latitude = ref_gps[0]
+        reference_navsat.longitude = ref_gps[1]
+        self.debug_splice_pt_publisher.publish(reference_navsat)
+        
+        
+        # generate new path
+        return Trajectory(json_filepath=None, positions=new_path)
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