OpenClaw AI Rock-Paper-Scissors Game Tutorial

Before starting, please complete [01-Peripheral Hardware Configuration], [02-OpenClaw Jetson-KEY Configuration], [03-OpenClaw Model Switching], [04-AI Voice Interaction Configuration], and [05-Three Dialogue Solution Configuration Tests] in the Pre-use Preparation directory. If you are only using TUI / WhatsApp, you can skip 04 for now. This article assumes the basic environment is already prepared and only covers the AI Rock-Paper-Scissors project itself.

1. Tutorial Objective

This article demonstrates OpenClaw's interactive gaming capability through "gesture recognition + AI referee + screen and light feedback". After completing this tutorial, readers can:

• Learn how to use the camera to recognize player gestures
• Interact with OpenClaw through three methods: WhatsApp, TUI, and voice code
• Complete four project scenarios: gesture recognition, AI move, result determination, score feedback

2. Hardware Preparation

• OpenClaw main control board
• CSI camera module
• OLED display
• RGB light strip / RGB LED module
• [Optional] AI voice module + speaker
• Wiring diagram

3. Software Preparation

Code entry points used in this tutorial

• Camera capture command: /home/jetson/hardware_hal_demo/seewhat
• Voice entry: /home/jetson/voice_to_openclaw/src/main.py

The key capabilities of this project mainly consist of three parts:

• The camera is responsible for capturing the player's gesture
• OpenClaw is responsible for deciding the AI's move and displaying the result on OLED / RGB

4. Testing Basic Project Capabilities

Before starting this project, please complete an openclaw tui basic dialogue self-check first; if you haven't done so, see [05-Three Dialogue Solution Configuration Tests] first. After passing, use TUI to verify the basic capabilities in the project.

Enter in terminal:

openclaw tui

Then you can start with a few basic tests:

• Take a photo of my gesture
• Check if this is a scissors gesture
• Display "Ready" on the OLED
• Light the RGB blue

5. Three Solutions for Communicating with OpenClaw

If you have selected the AI voice module + speaker, Feishu dialogue, tui, and whatsapp dialogue need to broadcast OpenClaw's replies. You can run the following program in the terminal. The AI voice module dialogue does not need to be run repeatedly.

• Modify the broadcast toggle parameter

xxxxxxxxxx
/home/jetson/voice_to_openclaw/.env

xxxxxxxxxx
ENABLE_TTS=true  #This parameter controls whether to broadcast. After modification, save and run the following program in the terminal

• Enter in terminal

xxxxxxxxxx
cd ~/voice_to_openclaw
source .venv/bin/activate
python -m src.openclaw_session_tts

5.1 WhatsApp Solution

For WhatsApp integration and bot creation steps, please refer directly to [05-Three Dialogue Solution Configuration Tests]. After creation, you can remotely trigger the Rock-Paper-Scissors game in WhatsApp, for example:

• Let's play Rock-Paper-Scissors, take a photo to recognize my gesture, you can randomly make a gesture, then judge whether you won or I won, OLED displays who won this round

You can add your own WhatsApp dialogue screenshots here.

5.2 TUI Solution

If you have completed the TUI self-check in the Prerequisites section, directly enter terminal text dialogue:

xxxxxxxxxx
openclaw tui

Then input project-related commands, for example:

• Let's play Rock-Paper-Scissors, you randomly make a gesture first, then take a photo to recognize my gesture, finally judge whether you won or I won, OLED displays who won this round, if you win light the running lights, if I win the servo performs a dance

5.3 Voice Code Solution

xxxxxxxxxx
Requires optional AI voice interaction module + speaker

For voice module installation, environment configuration, and basic wake-up process, please refer directly to [04-AI Voice Interaction Configuration]. After wake-up, you can directly speak control commands, for example:

• Let's play Rock-Paper-Scissors, take a photo to recognize my gesture, you can randomly make a gesture, then judge whether you won or I won, OLED displays who won this round

6. Project Implementation

Note: The following demonstrations are all conducted using the openclaw tui method. You can also choose WhatsApp or voice methods to complete them.

6.1 Scenario 1: Gesture Recognition

Experiment Objective

Recognize the gesture currently made by the player, such as rock, scissors, or paper.

Effect Description

OpenClaw will first take a photo, then identify the gesture type based on the image. This step provides the input for the entire game.

Example Commands

• Recognize the gesture I'm making now
• I've already made my move, check it for me
• Check if this is rock, scissors, or paper

6.2 Scenario 2: AI Move and Determination

Experiment Objective

After recognizing the player's gesture, have OpenClaw provide the AI's move result and determine the winner.

Effect Description

This step best demonstrates the "visual input + dialogue reasoning" feature. OpenClaw not only recognizes the player but also makes its own move, providing its own move and result explanation.

Example Commands

• Let's play Rock-Paper-Scissors, take a photo to recognize my gesture, you can randomly make a gesture, then judge whether you won or I won, OLED displays who won this round

6.3 Scenario 3: OLED Scoreboard

Experiment Objective

Have the OLED display the current round result or cumulative score.

Effect Description

The screen can display Win, Lose, Draw, or simple scores like You 1 : 0 AI, making the project more like a complete mini-game.

Example Commands

• Display this round's result on the OLED
• Write the score to the screen
• Display "Round 1 You Win"

6.4 Scenario 4: RGB Result Feedback

Experiment Objective

Use RGB colors to quickly express win/loss results.

Effect Description

For example, light green for a win, red for a loss, blue for a draw. This way, you can instantly see the round's result without reading any text.

Example Commands

• Light green if I win
• Light red if I lose
• If you win light the running lights, if I win the servo performs a dance