# Use Case: Smart Greenhouse with OpenClaw + Agent ROS Bridge

## Executive Summary

**Scenario:** A commercial greenhouse operation uses OpenClaw with Agent ROS Bridge to manage a fleet of ROS2-based agricultural robots through natural language commands.

**Value Proposition:** Farm workers can control complex robotic systems using simple conversational language, dramatically reducing training time and operational complexity.

---

## System Architecture

```
┌─────────────────────────────────────────────────────────────────┐
│                        USER INTERFACE                            │
│   OpenClaw Agent (Tablet/Phone)                                  │
│   "Check the tomatoes in Zone A"                                 │
└──────────────────────────┬──────────────────────────────────────┘
                           │ Natural Language
                           ▼
┌─────────────────────────────────────────────────────────────────┐
│                    AGENT ROS BRIDGE                              │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────────────┐  │
│  │ NL Interpreter│  │ Context Mgr  │  │ Fleet Intelligence   │  │
│  │ "tomatoes" → │  │ Learn zones  │  │ Assign best robot    │  │
│  │  /zone_a/tom │  │ Track state  │  │ to task              │  │
│  └──────────────┘  └──────────────┘  └──────────────────────┘  │
└──────────────────────────┬──────────────────────────────────────┘
                           │ ROS2 Commands
                           ▼
┌─────────────────────────────────────────────────────────────────┐
│                      GREENHOUSE ROS2 NETWORK                     │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────┐        │
│  │  Scout   │  │  Water   │  │  Harvest │  │  Patrol  │        │
│  │  Bot 1   │  │  Bot 2   │  │  Bot 3   │  │  Drone   │        │
│  │ (Cameras)│  │(Irrigate)│  │ (Pick)   │  │(Overview)│        │
│  └──────────┘  └──────────┘  └──────────┘  └──────────┘        │
└─────────────────────────────────────────────────────────────────┘
```

---

## The Greenhouse Setup

### Physical Layout

```
┌─────────────────────────────────────────────────────────────┐
│                        GREENHOUSE                            │
│                                                              │
│   ┌─────┐    ┌─────┐    ┌─────┐    ┌─────┐                │
│   │Zone │    │Zone │    │Zone │    │Zone │                │
│   │  A  │    │  B  │    │  C  │    │  D  │                │
│   │Tom. │    │Pepp.│    │Cuke.│    │Lett.│                │
│   │ 🍅  │    │ 🌶️  │    │ 🥒  │    │ 🥬  │                │
│   └─────┘    └─────┘    └─────┘    └─────┘                │
│                                                              │
│   Charging Station: [🔌]  Control Room: [🖥️]                │
│                                                              │
│   Water Stations: 💧 💧 💧                                  │
│   Tool Stations: 🔧 🔧                                      │
└─────────────────────────────────────────────────────────────┘
```

### Robot Fleet

| Robot | Type | ROS2 Topics | Capabilities |
|-------|------|-------------|--------------|
| **Scout-1** | Ground robot | `/scout1/camera`, `/scout1/odom` | Visual inspection, disease detection, growth monitoring |
| **Scout-2** | Ground robot | `/scout2/camera`, `/scout2/odom` | Same as Scout-1 |
| **Water-1** | Irrigation bot | `/water1/pump`, `/water1/flow` | Precision watering, nutrient delivery |
| **Harvest-1** | Picking arm | `/harvest1/arm`, `/harvest1/gripper` | Tomato/vegetable picking |
| **Drone-1** | Aerial | `/drone1/camera`, `/drone1/altitude` | Overview monitoring, thermal imaging |

---

## Day in the Life: Natural Language Operations

### Morning Routine (8:00 AM)

**Farm Manager:** "Good morning, what's the status of all robots?"

**OpenClaw:** "Good morning! Here's the fleet status:
- Scout-1: Active in Zone A, battery 85%
- Scout-2: Charging (completed overnight patrol)
- Water-1: Idle at charging station, 100% battery
- Harvest-1: Standby, ready for picking
- Drone-1: Offline (scheduled maintenance)"

### Crop Inspection (9:30 AM)

**Manager:** "Check the tomatoes in Zone A for any issues"

**OpenClaw:** "Sending Scout-1 to Zone A for tomato inspection..."

*[Scout-1 navigates to Zone A, captures images]*

**OpenClaw:** "Inspection complete. Found:
- 3 plants showing early signs of leaf discoloration (possible nutrient deficiency)
- 12 ripe tomatoes ready for harvest
- Soil moisture at 65% (optimal)
- No pest detected

Recommendations:
1. Apply nitrogen supplement to rows 3, 7, and 12
2. Schedule harvest for today afternoon
3. Continue current watering schedule"

### Irrigation Management (11:00 AM)

**Manager:** "Water Zone C cucumbers, they looked dry yesterday"

**OpenClaw:** "Zone C moisture level is currently 45% (below optimal 60%). Deploying Water-1 to Zone C with 15L precision irrigation..."

*[Water-1 navigates to Zone C, irrigates specific plants]*

**OpenClaw:** "Irrigation complete. Zone C moisture now at 68%. Water-1 returning to charging station."

### Harvesting (2:00 PM)

**Manager:** "Harvest all ripe vegetables in Zones A and B"

**OpenClaw:** "Analyzing crop readiness across Zones A and B...
- Zone A: 12 tomatoes ready
- Zone B: 8 peppers ready

Deploying Harvest-1 to Zone A first (closest), then Zone B. Estimated completion: 45 minutes."

*[Harvest-1 picks vegetables, places in collection bins]*

**OpenClaw:** "Harvest complete! Collected:
- 12 tomatoes (Zone A)
- 8 peppers (Zone B)
- Quality: 100% Grade A

Collection bins are at the north exit."

### Afternoon Patrol (4:00 PM)

**Manager:** "Patrol the entire greenhouse and report any issues"

**OpenClaw:** "Starting comprehensive patrol with Scout-2..."

*[Scout-2 systematically patrols all zones]*

**OpenClaw:** "Patrol complete. All zones normal except:
- Zone D: Temperature 2°C above optimal (check ventilation)
- North water station: Flow rate 10% below normal (check for blockage)

No critical issues detected."

---

## Technical Implementation

### 1. Initial Setup

```python
# Initialize Agent ROS Bridge for greenhouse
from agent_ros_bridge import Bridge
from agent_ros_bridge.integrations.openclaw_adapter import OpenClawAdapter

bridge = Bridge()
adapter = bridge.get_openclaw_adapter()

# Teach the system about greenhouse layout
adapter.learn_location("zone_a", {"x": 10, "y": 5})
adapter.learn_location("zone_b", {"x": 30, "y": 5})
adapter.learn_location("zone_c", {"x": 50, "y": 5})
adapter.learn_location("zone_d", {"x": 70, "y": 5})
adapter.learn_location("charging_station", {"x": 5, "y": 20})
adapter.learn_location("water_station_1", {"x": 25, "y": 20})
adapter.learn_location("water_station_2", {"x": 55, "y": 20})
adapter.learn_location("tool_station", {"x": 80, "y": 20})
adapter.learn_location("collection_point", {"x": 85, "y": 2})
```

### 2. Register Robot Fleet

```python
from agent_ros_bridge.integrations.fleet_intelligence import (
    FleetIntelligence, RobotState, RobotCapabilities
)

fleet = FleetIntelligence()

# Register each robot
fleet.update_robot_state(RobotState(
    robot_id="scout-1",
    name="Scout-1",
    status="idle",
    position={"x": 10, "y": 5},
    battery_percent=85,
    capabilities=RobotCapabilities(
        can_navigate=True,
        can_manipulate=False,
        can_carry=False
    )
))

# Similar for other robots...
```

### 3. Natural Language Commands

```python
# Example: Check tomatoes
result = await adapter.execute_nl(
    "Check the tomatoes in Zone A",
    session_id="greenhouse_manager"
)

# Example: Water cucumbers
result = await adapter.execute_nl(
    "Water Zone C cucumbers",
    session_id="greenhouse_manager"
)

# Example: Harvest
result = await adapter.execute_nl(
    "Harvest all ripe vegetables",
    session_id="greenhouse_manager"
)
```

### 4. ROS2 Integration

```yaml
# config/greenhouse.yaml
transports:
  websocket:
    port: 8765
    auth:
      enabled: true
      jwt_secret: ${JWT_SECRET}

ros2:
  namespace: "greenhouse"
  robots:
    scout-1:
      topics:
        camera: "/scout1/camera/image_raw"
        odometry: "/scout1/odom"
        status: "/scout1/status"
    water-1:
      topics:
        pump: "/water1/pump/control"
        flow: "/water1/flow_rate"
    harvest-1:
      topics:
        arm: "/harvest1/arm_controller"
        gripper: "/harvest1/gripper"
```

---

## Advanced Features

### 1. Autonomous Scheduling

```python
# Schedule daily patrol at 6 AM and 6 PM
from agent_ros_bridge.integrations.autonomous_behaviors import (
    MissionPlanner, PatrolRoute, Waypoint
)

planner = MissionPlanner()

# Define patrol route
patrol = PatrolRoute(
    name="daily_greenhouse_patrol",
    waypoints=[
        Waypoint(x=10, y=5, name="zone_a"),
        Waypoint(x=30, y=5, name="zone_b"),
        Waypoint(x=50, y=5, name="zone_c"),
        Waypoint(x=70, y=5, name="zone_d"),
    ],
    interval_minutes=720  # 12 hours
)

# Start autonomous patrol
behavior_manager.start_patrol(patrol, robot_id="scout-2")
```

### 2. Context-Aware Operations

```python
# System remembers previous commands
# Manager: "Check Zone A tomatoes"
# [Scout-1 goes to Zone A]

# Later...
# Manager: "Water them"  <- "them" refers to Zone A tomatoes
# System knows context and waters Zone A
```

### 3. Intelligent Robot Selection

```python
# "Harvest ripe tomatoes"
# System automatically:
# 1. Finds closest robot with harvesting capability
# 2. Checks battery levels
# 3. Assigns Harvest-1 (best suited)
# 4. Navigates to Zone A
```

### 4. Safety Features

```python
# "Move fast to Zone B"
# System responds:
# "Warning: High-speed movement requested. 
#  Workers detected in Zone B corridor. 
#  Proceed with caution?"
```

---

## Benefits

### For Farm Workers

| Before | After |
|--------|-------|
| Complex ROS2 command line | Natural language conversation |
| 2-week training required | 10-minute orientation |
| Manual robot control | Autonomous task execution |
| Constant monitoring | Automated patrols and alerts |

### For Operations

| Metric | Improvement |
|--------|-------------|
| Crop inspection frequency | 4x increase |
| Water usage | 30% reduction (precision) |
| Harvest timing | 100% optimal ripeness |
| Labor costs | 40% reduction |
| Disease detection | 5x faster |

### ROI Calculation

```
Initial Investment:
- Agent ROS Bridge setup: $5,000
- Robot fleet (5 units): $150,000
- Integration & training: $10,000
Total: $165,000

Annual Savings:
- Labor reduction: $60,000/year
- Water efficiency: $15,000/year
- Reduced crop loss: $25,000/year
Total: $100,000/year

Payback Period: 1.65 years
5-Year ROI: 303%
```

---

## Sample Conversation Log

```
[08:15] Manager: "Status report"
[08:15] OpenClaw: "All systems operational. Scout-1 in Zone A, 
          others charging. No alerts."

[09:30] Manager: "Check tomatoes"
[09:30] OpenClaw: "Deploying Scout-1 to Zone A..."
[09:35] OpenClaw: "Found 12 ripe tomatoes, 3 need nutrients. 
          Recommend fertilizing rows 3, 7, 12."

[09:40] Manager: "Apply fertilizer to those rows"
[09:40] OpenClaw: "Water-1 equipped with fertilizer. 
          Treating rows 3, 7, 12..."
[09:55] OpenClaw: "Fertilization complete."

[14:00] Manager: "Harvest everything ready"
[14:00] OpenClaw: "Harvest-1 deployed. Picking 12 tomatoes, 8 peppers..."
[14:45] OpenClaw: "Harvest complete. 20 items collected. 
          Bins at north exit."

[16:00] Manager: "Any issues today?"
[16:00] OpenClaw: "Minor: Zone D +2°C (check vents), 
          Water Station 1 flow reduced 10%. 
          Otherwise all good."
```

---

## Deployment Guide

### Step 1: Install Agent ROS Bridge

```bash
pip install agent-ros-bridge
export JWT_SECRET=$(openssl rand -base64 32)
agent-ros-bridge --config greenhouse.yaml
```

### Step 2: Configure OpenClaw Skill

```bash
# Package and install skill
cd skills/agent-ros-bridge
python scripts/package_skill.py
# Upload to ClawHub or install locally
```

### Step 3: Connect Robots

```bash
# Each robot connects to Agent ROS Bridge
ros2 run scout_bot scout_node --ros-args \
  -p bridge_host:=localhost \
  -p bridge_port:=8765
```

### Step 4: Start Managing

Open OpenClaw interface and start giving natural language commands!

---

## Conclusion

This use case demonstrates how **OpenClaw + Agent ROS Bridge** transforms complex robotic greenhouse operations into simple conversational interactions.

**Key Wins:**
- ✅ No ROS2 expertise required for operators
- ✅ Natural language control of entire fleet
- ✅ Context-aware, intelligent automation
- ✅ Significant operational cost savings
- ✅ Improved crop quality and yield

**The future of agriculture is conversational.**
