---
pattern_id: pattern_mobilevla_cot
applicable_symptoms: [mobilevla_cot]
domain: Memory_Reasoning
---

# Embodied agents lack structured reasoning to align language, vision, and action modalities, leading to poor generalization in long-horizon tasks.

**Domain**: `Memory_Reasoning`

## Fix

Use multi-granularity chain-of-thought (CoT) reasoning supervision in a large-scale dataset to align language, vision, and action modalities.

## Anti-pattern

Training without explicit CoT reasoning supervision fails to align modalities effectively.

## Cross-domain analogies

- **Perception_Vision** → Map language, vision, and action into a unified 3D voxel grid for joint structured reasoning.
  - related fix: Voxelize the physical world into structured 3D cells and aggregate multi-view 2D features into that unified 3D space via 2D-3D spatial sampling, then jointly predict 3D occupancy, room layout, and bounding boxes through multi-task learning.
- **Planning_Decision** → Benchmark-driven structured reasoning to align modalities across long horizons.
  - related fix: NavSpace benchmark with spatial intelligence instructions and evaluation metrics that test object-relationship and layout reasoning.
- **Learning_Training** → Pretrain a multimodal alignment model on diverse data to ground reasoning across modalities.
  - related fix: Pretrain a vision-language model on large-scale web data to learn cross-modal alignment, then fine-tune on navigation tasks

## Patch

```diff
--- mobilevla_cot.before.py
+++ mobilevla_cot.after.py
@@ -1,2 +1,4 @@
-# --- BEFORE (vulnerable to the symptom below) ---

+# --- AFTER (ROSCLAW heuristic graft) ---

 # Symptom: Embodied agents lack structured reasoning to align language, vision, and action modalities, leading to poor generalization in long-horizon tasks.

+# Fix    : Use multi-granularity chain-of-thought (CoT) reasoning supervision in a large-scale dataset to align language, vision, and action modalities.

+# Avoid  : Training without explicit CoT reasoning supervision fails to align modalities effectively.

```
