diff --git a/newton/_src/sensors/sensor_contact.py b/newton/_src/sensors/sensor_contact.py
index 942e004967..4c22b0a670 100644
--- a/newton/_src/sensors/sensor_contact.py
+++ b/newton/_src/sensors/sensor_contact.py
@@ -304,12 +304,6 @@ def __init__(
             c_shapes = [self.ObjectType.TOTAL]
             c_bodies = []
 
-        contact_pairs = (
-            set(map(tuple, model.shape_contact_pairs.list()))
-            if getattr(model, "shape_contact_pairs", None) is not None
-            else None
-        )
-
         TOTAL = self.ObjectType.TOTAL
         wc = model.world_count
         shape_ws = model.shape_world_start.list()
@@ -332,13 +326,65 @@ def bucket(indices, ws):
         c_body_b, c_body_g = bucket(c_bodies, body_ws)
         c_shape_b, c_shape_g = bucket(c_shapes, shape_ws)
 
+        _homogeneous = wc > 1 and (
+            len(set(body_ws[i + 1] - body_ws[i] for i in range(wc))) == 1
+            and len(set(shape_ws[i + 1] - shape_ws[i] for i in range(wc))) == 1
+            and all(len(s_body_b[w]) == len(s_body_b[0]) for w in range(1, wc))
+            and all(len(s_shape_b[w]) == len(s_shape_b[0]) for w in range(1, wc))
+            and all(len(c_body_b[w]) == len(c_body_b[0]) for w in range(1, wc))
+            and all(len(c_shape_b[w]) == len(c_shape_b[0]) for w in range(1, wc))
+        )
+
+        if getattr(model, "shape_contact_pairs", None) is not None:
+            if _homogeneous and wc > 1:
+                import numpy as np
+                cp_np = model.shape_contact_pairs.numpy()
+                lo, hi = shape_ws[0], shape_ws[1]
+                mask = (cp_np[:, 0] >= lo) & (cp_np[:, 0] < hi) & (cp_np[:, 1] >= lo) & (cp_np[:, 1] < hi)
+                contact_pairs = set(map(tuple, cp_np[mask].tolist()))
+            else:
+                contact_pairs = set(map(tuple, model.shape_contact_pairs.numpy()))
+        else:
+            contact_pairs = None
+
         per_world_results = []
-        for w in range(wc):
-            wb = ([TOTAL] if TOTAL in c_bodies else []) + c_body_g + c_body_b[w]
-            wsh = ([TOTAL] if TOTAL in c_shapes else []) + c_shape_g + c_shape_b[w]
-            per_world_results.append(
-                self._assemble_sensor_mappings(s_body_b[w], s_shape_b[w], wb, wsh, model.body_shapes, contact_pairs)
+        if _homogeneous:
+            wb0 = ([TOTAL] if TOTAL in c_bodies else []) + c_body_g + c_body_b[0]
+            wsh0 = ([TOTAL] if TOTAL in c_shapes else []) + c_shape_g + c_shape_b[0]
+            r0 = self._assemble_sensor_mappings(
+                s_body_b[0], s_shape_b[0], wb0, wsh0, model.body_shapes, contact_pairs
             )
+            sp0, raw0, n_readings0, counter_idx0, so_kinds0, cp_kinds0 = r0
+
+            for w in range(wc):
+                b_off = body_ws[w] - body_ws[0]
+                s_off = shape_ws[w] - shape_ws[0]
+
+                sp_w = [(a + s_off if a >= 0 else a, b + s_off if b >= 0 else b) for a, b in sp0]
+
+                so_w = []
+                for idx, kind in so_kinds0:
+                    off = b_off if kind == self.ObjectType.BODY else s_off
+                    so_w.append((idx + off, kind))
+
+                cp_w = []
+                for idx, kind in cp_kinds0:
+                    if kind == TOTAL:
+                        cp_w.append((idx, kind))
+                    else:
+                        off = b_off if kind == self.ObjectType.BODY else s_off
+                        cp_w.append((idx + off, kind))
+
+                per_world_results.append((sp_w, raw0, n_readings0, counter_idx0, so_w, cp_w))
+        else:
+            for w in range(wc):
+                wb = ([TOTAL] if TOTAL in c_bodies else []) + c_body_g + c_body_b[w]
+                wsh = ([TOTAL] if TOTAL in c_shapes else []) + c_shape_g + c_shape_b[w]
+                per_world_results.append(
+                    self._assemble_sensor_mappings(
+                        s_body_b[w], s_shape_b[w], wb, wsh, model.body_shapes, contact_pairs
+                    )
+                )
 
         max_r = max((r[2] for r in per_world_results), default=0)
         self.sensing_objs = [r[4] for r in per_world_results]