diff --git a/orx-jvm/orx-triangulation/src/demo/kotlin/DemoDelaunay01.kt b/orx-jvm/orx-triangulation/src/demo/kotlin/DemoDelaunay01.kt
index 0c969266..b58da029 100644
--- a/orx-jvm/orx-triangulation/src/demo/kotlin/DemoDelaunay01.kt
+++ b/orx-jvm/orx-triangulation/src/demo/kotlin/DemoDelaunay01.kt
@@ -22,7 +22,7 @@ fun main() {
 
             val circle = Circle(Vector2(400.0), 250.0)
 
-            val points = poissonDiskSampling(width * 1.0, height * 1.0, 30.0)
+            val points = poissonDiskSampling(drawer.bounds, 30.0)
                 .filter { circle.contains(it) }
 
             val delaunay = Delaunay.from(points + circle.contour.equidistantPositions(40))
diff --git a/orx-jvm/orx-triangulation/src/demo/kotlin/DemoDelaunay02.kt b/orx-jvm/orx-triangulation/src/demo/kotlin/DemoDelaunay02.kt
index f6daef84..e994c33a 100644
--- a/orx-jvm/orx-triangulation/src/demo/kotlin/DemoDelaunay02.kt
+++ b/orx-jvm/orx-triangulation/src/demo/kotlin/DemoDelaunay02.kt
@@ -21,7 +21,7 @@ fun main() {
 
             val frame = Rectangle.fromCenter(Vector2(400.0), 600.0, 600.0)
 
-            val points = poissonDiskSampling(frame.width, frame.height, 50.0).map { it + frame.corner }
+            val points = poissonDiskSampling(frame, 50.0).map { it + frame.corner }
 
             val delaunay = Delaunay.from(points)
             val halfedges = delaunay.halfedges()
diff --git a/orx-jvm/orx-triangulation/src/demo/kotlin/DemoVoronoi01.kt b/orx-jvm/orx-triangulation/src/demo/kotlin/DemoVoronoi01.kt
index e53a5a9e..11603a3f 100644
--- a/orx-jvm/orx-triangulation/src/demo/kotlin/DemoVoronoi01.kt
+++ b/orx-jvm/orx-triangulation/src/demo/kotlin/DemoVoronoi01.kt
@@ -23,7 +23,7 @@ fun main() {
             val circle = Circle(Vector2(400.0), 250.0)
             val frame = Rectangle.fromCenter(Vector2(400.0), 600.0, 600.0)
 
-            val points = poissonDiskSampling(width * 1.0, height * 1.0, 30.0)
+            val points = poissonDiskSampling(drawer.bounds, 30.0)
                 .filter { circle.contains(it) }
 
             val delaunay = Delaunay.from(points + circle.contour.equidistantPositions(40))
diff --git a/orx-noise/src/commonMain/kotlin/PoissonDisk.kt b/orx-noise/src/commonMain/kotlin/PoissonDisk.kt
index 0bfdfd7f..181abb0d 100644
--- a/orx-noise/src/commonMain/kotlin/PoissonDisk.kt
+++ b/orx-noise/src/commonMain/kotlin/PoissonDisk.kt
@@ -20,11 +20,12 @@ internal const val epsilon = 0.0000001
  * They can also be generated on a ring like in the original algorithm from Robert Bridson
  *
  * @param bounds the rectangular bounds of the area to generate points in
- * @param r the minimum distance between each point
+ * @param radius the minimum distance between each point
  * @param tries number of candidates per point
  * @param randomOnRing generate random points on a ring with an annulus from r to 2r
  * @param random a random number generator, default value is [Random.Default]
  * @param initialPoints a list of points in sampler space, these points will not be tested against [r]
+ * @param obstacleHashGrids a list of obstacles to avoid, defined by points and radii
  * @param boundsMapper a custom function to check if a point is within bounds
 
  * @return a list of points