diff --git a/gtsam/geometry/SOn-inl.h b/gtsam/geometry/SOn-inl.h
index 1c05eac47..344822c1f 100644
--- a/gtsam/geometry/SOn-inl.h
+++ b/gtsam/geometry/SOn-inl.h
@@ -36,15 +36,18 @@ typename SO<N>::TangentVector SO<N>::Vee(const MatrixNN& X) {
 
 template <int N>
 SO<N> SO<N>::ChartAtOrigin::Retract(const TangentVector& xi, ChartJacobian H) {
+  if (H) throw std::runtime_error("SO<N>::Retract jacobian not implemented.");
   const Matrix X = Hat(xi / 2.0);
   size_t n = AmbientDim(xi.size());
   const auto I = Eigen::MatrixXd::Identity(n, n);
+  // https://pdfs.semanticscholar.org/6165/0347b2ccac34b5f423081d1ce4dbc4d09475.pdf
   return SO((I + X) * (I - X).inverse());
 }
 
 template <int N>
 typename SO<N>::TangentVector SO<N>::ChartAtOrigin::Local(const SO& R,
                                                           ChartJacobian H) {
+  if (H) throw std::runtime_error("SO<N>::Local jacobian not implemented.");
   const size_t n = R.rows();
   const auto I = Eigen::MatrixXd::Identity(n, n);
   const Matrix X = (I - R.matrix_) * (I + R.matrix_).inverse();
@@ -87,9 +90,11 @@ typename SO<N>::VectorN2 SO<N>::vec(
   VectorN2 X(n2);
   X << Eigen::Map<const Matrix>(matrix_.data(), n2, 1);
 
-  // If requested, calculate H as (I \oplus Q) * P
+  // If requested, calculate H as (I \oplus Q) * P,
+  // where Q is the N*N rotation matrix, and P is calculated below.
   if (H) {
     // Calculate P matrix of vectorized generators
+    // TODO(duy): Should we refactor this as the jacobian of Hat?
     const size_t d = dim();
     Matrix P(n2, d);
     for (size_t j = 0; j < d; j++) {
diff --git a/gtsam/geometry/SOn.h b/gtsam/geometry/SOn.h
index 06031b093..7954c4d6c 100644
--- a/gtsam/geometry/SOn.h
+++ b/gtsam/geometry/SOn.h
@@ -11,8 +11,7 @@
 
 /**
  * @file    SOn.h
- * @brief   n*n matrix representation of SO(n), template on N, which can be
- * Eigen::Dynamic
+ * @brief   N*N matrix representation of SO(N). N can be Eigen::Dynamic
  * @author  Frank Dellaert
  * @date    March 2019
  */
@@ -43,7 +42,7 @@ constexpr int NSquaredSO(int N) { return (N < 0) ? Eigen::Dynamic : N * N; }
 
 /**
  * Manifold of special orthogonal rotation matrices SO<N>.
- * Template paramater N can be a fizxed integer or can be Eigen::Dynamic
+ * Template paramater N can be a fixed integer or can be Eigen::Dynamic
  */
 template <int N>
 class SO : public LieGroup<SO<N>, internal::DimensionSO(N)> {
@@ -53,7 +52,6 @@ class SO : public LieGroup<SO<N>, internal::DimensionSO(N)> {
   using VectorN2 = Eigen::Matrix<double, internal::NSquaredSO(N), 1>;
   using MatrixDD = Eigen::Matrix<double, dimension, dimension>;
 
- public:
   EIGEN_MAKE_ALIGNED_OPERATOR_NEW
 
  protected:
@@ -100,7 +98,7 @@ class SO : public LieGroup<SO<N>, internal::DimensionSO(N)> {
 
   /// Constructor from AngleAxisd
   template <int N_ = N, typename = IsSO3<N_>>
-  SO(const Eigen::AngleAxisd& angleAxis) : matrix_(angleAxis) {}
+  explicit SO(const Eigen::AngleAxisd& angleAxis) : matrix_(angleAxis) {}
 
   /// Constructor from axis and angle. Only defined for SO3
   static SO AxisAngle(const Vector3& axis, double theta);
@@ -117,7 +115,7 @@ class SO : public LieGroup<SO<N>, internal::DimensionSO(N)> {
   template <int N_ = N, typename = IsDynamic<N_>>
   static SO Random(boost::mt19937& rng, size_t n = 0) {
     if (n == 0) throw std::runtime_error("SO: Dimensionality not known.");
-    // This needs to be re-thought!
+    // TODO(frank): This needs to be re-thought!
     static boost::uniform_real<double> randomAngle(-M_PI, M_PI);
     const size_t d = SO::Dimension(n);
     Vector xi(d);
diff --git a/gtsam/geometry/tests/testRot3.cpp b/gtsam/geometry/tests/testRot3.cpp
index 0365bc659..c95b85f21 100644
--- a/gtsam/geometry/tests/testRot3.cpp
+++ b/gtsam/geometry/tests/testRot3.cpp
@@ -647,7 +647,6 @@ TEST(Rot3 , ChartDerivatives) {
 
 /* ************************************************************************* */
 TEST(Rot3, ClosestTo) {
-  // Example top-left of SO(4) matrix not quite on SO(3) manifold
   Matrix3 M;
   M << 0.79067393, 0.6051136, -0.0930814,   //
       0.4155925, -0.64214347, -0.64324489,  //
diff --git a/gtsam/geometry/tests/testSO3.cpp b/gtsam/geometry/tests/testSO3.cpp
index 3c5b947ba..b2c781b35 100644
--- a/gtsam/geometry/tests/testSO3.cpp
+++ b/gtsam/geometry/tests/testSO3.cpp
@@ -15,10 +15,12 @@
  * @author Frank Dellaert
  **/
 
-#include <CppUnitLite/TestHarness.h>
+#include <gtsam/geometry/SO3.h>
+
 #include <gtsam/base/Testable.h>
 #include <gtsam/base/testLie.h>
-#include <gtsam/geometry/SO3.h>
+
+#include <CppUnitLite/TestHarness.h>
 
 using namespace std;
 using namespace gtsam;
@@ -51,7 +53,6 @@ TEST(SO3, Constructors) {
 
 /* ************************************************************************* */
 TEST(SO3, ClosestTo) {
-  // Example top-left of SO(4) matrix not quite on SO(3) manifold
   Matrix3 M;
   M << 0.79067393, 0.6051136, -0.0930814,   //
       0.4155925, -0.64214347, -0.64324489,  //
diff --git a/gtsam/geometry/tests/testSOn.cpp b/gtsam/geometry/tests/testSOn.cpp
index 384150c52..4e5f12c0c 100644
--- a/gtsam/geometry/tests/testSOn.cpp
+++ b/gtsam/geometry/tests/testSOn.cpp
@@ -39,6 +39,17 @@
 using namespace std;
 using namespace gtsam;
 
+//******************************************************************************
+// Test dhynamic with n=0
+TEST(SOn, SO0) {
+  const auto R = SOn(0);
+  EXPECT_LONGS_EQUAL(0, R.rows());
+  EXPECT_LONGS_EQUAL(Eigen::Dynamic, SOn::dimension);
+  EXPECT_LONGS_EQUAL(Eigen::Dynamic, SOn::Dim());
+  EXPECT_LONGS_EQUAL(0, R.dim());
+  EXPECT_LONGS_EQUAL(-1, traits<SOn>::GetDimension(R));
+}
+
 //******************************************************************************
 TEST(SOn, SO5) {
   const auto R = SOn(5);
diff --git a/gtsam/slam/KarcherMeanFactor.h b/gtsam/slam/KarcherMeanFactor.h
index d0f2f57db..c098c9665 100644
--- a/gtsam/slam/KarcherMeanFactor.h
+++ b/gtsam/slam/KarcherMeanFactor.h
@@ -12,7 +12,7 @@
 /*
  * @file KarcherMeanFactor.h
  * @author Frank Dellaert
- * @date March 2019ƒ
+ * @date March 2019
  */
 
 #pragma once
@@ -26,18 +26,18 @@
 namespace gtsam {
 /**
  * Optimize for the Karcher mean, minimizing the geodesic distance to each of
- * the given rotations, ,by constructing a factor graph out of simple
+ * the given rotations, by constructing a factor graph out of simple
  * PriorFactors.
  */
 template <class T>
 T FindKarcherMean(const std::vector<T>& rotations);
 
 /**
- * The KarcherMeanFactor creates a constraint on all SO(3) variables with
+ * The KarcherMeanFactor creates a constraint on all SO(n) variables with
  * given keys that the Karcher mean (see above) will stay the same. Note the
  * mean itself is irrelevant to the constraint and is not a parameter: the
  * constraint is implemented as enforcing that the sum of local updates is
- * equal to zero, hence creating a rank-3 constraint. Note it is implemented as
+ * equal to zero, hence creating a rank-dim constraint. Note it is implemented as
  * a soft constraint, as typically it is used to fix a gauge freedom.
  * */
 template <class T>
@@ -67,4 +67,4 @@ class KarcherMeanFactor : public NonlinearFactor {
   }
 };
 // \KarcherMeanFactor
-}  // namespace gtsam
\ No newline at end of file
+}  // namespace gtsam