---
pattern_id: pattern_lovon
applicable_symptoms: [lovon]
domain: Perception_Vision
---

# Visual jittering due to gait and terrain degrades detection and tracking on legged robots during long-range navigation.

**Domain**: `Perception_Vision`

## Fix

Apply Laplacian Variance Filtering to stabilize camera feed before detection.

## Cross-domain analogies

- **Planning_Decision** → Use continuous low-level control to smooth visual input via adaptive gait stabilization.
  - related fix: Use continuous action spaces with low-level controllers (e.g., PID) and train with reinforcement learning or imitation learning on continuous trajectories.
- **Learning_Training** → Use synthetic visual jitter data from terrain models to augment training for robust perception.
  - related fix: Train a speaker model to generate synthetic instruction–trajectory pairs from unannotated visual paths, then augment the original training set with these synthetic pairs.
- **Control_Locomotion** → Use reinforcement learning to directly map gait-phase and terrain features to jitter-compensating camera control actions.
  - related fix: Use reinforcement learning to learn a control policy that directly maps sensor observations to actuator commands for plasma shape and position control.

## Patch

```diff
--- lovon.before.py
+++ lovon.after.py
@@ -1,2 +1,3 @@
-# --- BEFORE (vulnerable to the symptom below) ---

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

 # Symptom: Visual jittering due to gait and terrain degrades detection and tracking on legged robots during long-range navigation.

+# Fix    : Apply Laplacian Variance Filtering to stabilize camera feed before detection.

```
