diff --git a/nav2_smac_planner/include/nav2_smac_planner/node_lattice.hpp b/nav2_smac_planner/include/nav2_smac_planner/node_lattice.hpp
index b0b5ce6315..6763b52f30 100644
--- a/nav2_smac_planner/include/nav2_smac_planner/node_lattice.hpp
+++ b/nav2_smac_planner/include/nav2_smac_planner/node_lattice.hpp
@@ -111,6 +111,7 @@ struct LatticeMotionTable
   std::vector<TrigValues> trig_values;
   std::string current_lattice_filepath;
   LatticeMetadata lattice_metadata;
+  MotionModel motion_model = MotionModel::UNKNOWN;
 };
 
 /**
diff --git a/nav2_smac_planner/src/analytic_expansion.cpp b/nav2_smac_planner/src/analytic_expansion.cpp
index 23e94cadcd..2a0acab61e 100644
--- a/nav2_smac_planner/src/analytic_expansion.cpp
+++ b/nav2_smac_planner/src/analytic_expansion.cpp
@@ -108,9 +108,12 @@ typename AnalyticExpansion<NodeT>::NodePtr AnalyticExpansion<NodeT>::tryAnalytic
         }
 
         // The analytic expansion can short-cut near obstacles when closer to a goal
-        // So, we can attempt to refine it more by increasing the possible curvature
+        // So, we can attempt to refine it more by increasing the possible radius
         // higher than the minimum turning radius and use the best solution based on
         // a scoring function similar to that used in traveral cost estimation.
+
+        // TODO continue to search and compare?
+        // TODO take original and patch up: curve fitting path minimize curvature?
         auto scoringFn = [&](const AnalyticExpansionNodes & expansion) {
           if (expansion.size() < 2) {
             return std::numeric_limits<float>::max();
@@ -118,36 +121,37 @@ typename AnalyticExpansion<NodeT>::NodePtr AnalyticExpansion<NodeT>::tryAnalytic
 
           float score = 0.0;
           float normalized_cost = 0.0;
+          // Analytic expansions are consistently spaced
           const float distance = hypotf(
             expansion[1].proposed_coords.x - expansion[0].proposed_coords.x,
             expansion[1].proposed_coords.y - expansion[0].proposed_coords.y);
           const float & weight = expansion[0].node->motion_table.cost_penalty;
           for (auto iter = expansion.begin(); iter != expansion.end(); ++iter) {
             normalized_cost = iter->node->getCost() / 252.0f;
-            // H-cost method
-            score += distance * (1.0 + weight * normalized_cost); // TODO quadratic option, add `* normalized_cost`
-            // Cost-only method
-            // score += normalized_cost;
+            // Search's Traversal Cost Function
+            score += distance * (1.0 + weight * normalized_cost);
           }
           return score;
-          // return score / expansion.size();
         };
 
         float best_score = scoringFn(analytic_nodes);
         float score = std::numeric_limits<float>::max();
         float min_turn_rad = node->motion_table.min_turning_radius;
-        const float step = 0.2; // TODO make proportional to resolution or parameter? In grid coords
-        unsigned int i = 0;
-        while (i < 20) {  // TODO what max to check?
-          min_turn_rad += step;
-          auto state_space = std::make_shared<ompl::base::DubinsStateSpace>(min_turn_rad);  // TODO set based on motion model
-          refined_analytic_nodes = getAnalyticPath(node, goal_node, getter, state_space);  // TODO other types of splines?
+        const float max_min_turn_rad = 4.0 * min_turn_rad;  // Up to 4x the turning radius
+        while (min_turn_rad < max_min_turn_rad) {
+          min_turn_rad += 0.5;  // In Grid Coords, 1/2 cell steps
+          ompl::base::StateSpacePtr state_space;
+          if (node->motion_table.motion_model == MotionModel::DUBIN) {
+            state_space = std::make_shared<ompl::base::DubinsStateSpace>(min_turn_rad);
+          } else {
+            state_space = std::make_shared<ompl::base::ReedsSheppStateSpace>(min_turn_rad);
+          }
+          refined_analytic_nodes = getAnalyticPath(node, goal_node, getter, state_space);
           score = scoringFn(refined_analytic_nodes);
           if (score <= best_score) {
             analytic_nodes = refined_analytic_nodes;
             best_score = score;
           }
-          i++;
         }
 
         return setAnalyticPath(node, goal_node, analytic_nodes);
diff --git a/nav2_smac_planner/src/node_lattice.cpp b/nav2_smac_planner/src/node_lattice.cpp
index dc6309edd1..d34ffc8552 100644
--- a/nav2_smac_planner/src/node_lattice.cpp
+++ b/nav2_smac_planner/src/node_lattice.cpp
@@ -80,9 +80,11 @@ void LatticeMotionTable::initMotionModel(
     if (!allow_reverse_expansion) {
       state_space = std::make_shared<ompl::base::DubinsStateSpace>(
         lattice_metadata.min_turning_radius);
+      motion_model = MotionModel::DUBIN;
     } else {
       state_space = std::make_shared<ompl::base::ReedsSheppStateSpace>(
         lattice_metadata.min_turning_radius);
+      motion_model = MotionModel::REEDS_SHEPP;
     }
   }
 
@@ -424,9 +426,11 @@ void NodeLattice::precomputeDistanceHeuristic(
   if (!search_info.allow_reverse_expansion) {
     motion_table.state_space = std::make_shared<ompl::base::DubinsStateSpace>(
       search_info.minimum_turning_radius);
+      motion_table.motion_model = MotionModel::DUBIN;
   } else {
     motion_table.state_space = std::make_shared<ompl::base::ReedsSheppStateSpace>(
       search_info.minimum_turning_radius);
+      motion_table.motion_model = MotionModel::REEDS_SHEPP;
   }
   motion_table.lattice_metadata =
     LatticeMotionTable::getLatticeMetadata(search_info.lattice_filepath);