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OpenClaw

fsd-secure

Full Self-Driving agent with highest safety standards (Camera-Only, Redundant Checks).

aadipapp0 installations selon la source☆ 0 Étoiles du dépôtv0.1.0

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install aadipapp/fsd-secure-skill

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

FSD Secure Skill

This skill implements a Camera-Only Full Self-Driving agent designed for maximum safety. It runs in a simulated environment and uses Dual-Pass Analysis to verify clear paths.

Safety Features

  • Dual-Pass Verification: Two independent algorithms must agree the path is clear.
  • Temporal Consistency: Requires 3 consecutive safe frames before acceleration.
  • Fail-Safe: Any uncertainty triggers an immediate Emergency Stop.

Commands

  • drive: Start the autonomous driving simulation.

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/aadipapp/fsd-secure-skill
Version
0.1.0
Commit
b46f0e5578ca3f123045eb4a4879c9ed9af45551
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

README

FSD Secure Skill (Camera-Only)

This skill simulates a "Highest Safety" autonomous driving agent that relies solely on visual data from cameras.

Safety Architecture

  1. Dual-Pass Verification: Every frame is analyzed by two independent systems:
    • Pass 1: Deep Neural Network (simulated) for high-level object detection.
    • Pass 2: Heuristic/Classical CV (simulated) for low-level edge/obstacle verification.
    • Requirement: Both must verify a clear path.
  2. Temporal Consistency: The agent will never accelerate unless the path has been verified clear for 3 consecutive frames. This prevents "flickering" false positives.
  3. Strict Confidence: Neural network confidence must exceed 99%.

Usage

Run the simulation:

python3 scripts/fsd_agent.py

The output will show the frame-by-frame analysis and the "Emergency Stop" triggers if any safety check fails.

Publishing

clawhub publish

Contenu extrait

SKILL.md
# FSD Secure Skill

This skill implements a **Camera-Only Full Self-Driving** agent designed for maximum safety.
It runs in a simulated environment and uses **Dual-Pass Analysis** to verify clear paths.

## Safety Features
- **Dual-Pass Verification**: Two independent algorithms must agree the path is clear.
- **Temporal Consistency**: Requires 3 consecutive safe frames before acceleration.
- **Fail-Safe**: Any uncertainty triggers an immediate Emergency Stop.

## Commands

- `drive`: Start the autonomous driving simulation.
README
# FSD Secure Skill (Camera-Only)

This skill simulates a "Highest Safety" autonomous driving agent that relies solely on visual data from cameras.

## Safety Architecture
1.  **Dual-Pass Verification**: Every frame is analyzed by two independent systems:
    -   **Pass 1**: Deep Neural Network (simulated) for high-level object detection.
    -   **Pass 2**: Heuristic/Classical CV (simulated) for low-level edge/obstacle verification.
    -   **Requirement**: Both must verify a clear path.
2.  **Temporal Consistency**: The agent will **never** accelerate unless the path has been verified clear for **3 consecutive frames**. This prevents "flickering" false positives.
3.  **Strict Confidence**: Neural network confidence must exceed **99%**.

## Usage

Run the simulation:
```bash
python3 scripts/fsd_agent.py
```

The output will show the frame-by-frame analysis and the "Emergency Stop" triggers if any safety check fails.

## Publishing
```bash
clawhub publish
```

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