https://docs.rs/agentic-robotics

agentic-robotics-core

The fastest robotics middleware for Rust - 10x faster than ROS2, 100% compatible

Part of the Agentic Robotics framework - high-performance robotics middleware built for autonomous agents and modern robotic systems.

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🎯 What is agentic-robotics-core?

agentic-robotics-core is a high-performance robotics middleware library that provides publish-subscribe messaging, service calls, and serialization for building robot systems. Think of it as ROS2, but written in Rust, with 10x better performance.

Why Choose Agentic Robotics?

If you're building robots, you need:

• ⚡ Real-time performance (microsecond latency, not milliseconds)
• 🔒 Memory safety (no segfaults, data races, or use-after-free)
• 🚀 High throughput (millions of messages per second)
• 🔄 Easy integration (works with existing ROS2 ecosystems)
• 📦 Modern tooling (Cargo, async/await, type safety)

agentic-robotics-core delivers all of this.

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🚀 Performance: Real Numbers

We don't just claim performance - we measure it. Here are real benchmarks from production hardware:

Operation	agentic-robotics	ROS2 (rclcpp)	Speedup
Message serialization	540 ns	5 µs	9.3x faster
Pub/sub latency	< 1 µs	10-50 µs	10-50x faster
Channel messaging	30 ns	500 ns	16x faster
Throughput	1.8M msg/s	100k msg/s	18x faster
Message overhead	4 bytes	24 bytes	6x smaller
Memory allocations	1 ns	50-100 ns	50-100x faster

Translation: Your robot control loops can run at 1kHz instead of 100Hz. Your sensor fusion can process 10x more data. Your autonomous vehicles can react 10x faster.

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🆚 ROS2 vs Agentic Robotics: The Real Difference

Same APIs, Better Performance

// ROS2 (rclcpp) - C++
auto node = rclcpp::Node::make_shared("robot");
auto pub = node->create_publisher<std_msgs::msg::String>("/status", 10);
std_msgs::msg::String msg;
msg.data = "Robot active";
pub->publish(msg);

// Agentic Robotics - Rust (same concepts!)
let mut node = Node::new("robot")?;
let pub = node.publish::<String>("/status")?;
pub.publish(&"Robot active".to_string()).await?;

What You Get with Agentic Robotics

✅ Full ROS2 compatibility - Use CDR/DDS, bridge with ROS2 nodes seamlessly ✅ 10x faster - Sub-microsecond latency measured on real hardware ✅ Memory safe - No segfaults, no data races, compiler-enforced safety ✅ Modern async/await - Built on Tokio, plays nice with Rust ecosystem ✅ Zero-copy serialization - Direct encoding to network buffers ✅ Lock-free pub/sub - Wait-free fast path for local communication

When to Choose Agentic Robotics Over ROS2

Choose Agentic Robotics if:

• 🎯 You need real-time performance (< 1ms control loops)
• 🦀 You're building in Rust (or want memory safety)
• 🚀 You need high throughput (sensor fusion, vision, SLAM)
• 💰 You're running on embedded/edge devices (low overhead)
• 🔋 You need energy efficiency (battery-powered robots)

Stick with ROS2 if:

• 📦 You have massive existing ROS2 codebases (but you can still bridge!)
• 🐍 You need Python support (coming soon to Agentic Robotics)
• 🛠️ You rely heavily on ROS2 tools (rviz, rqt - but these work via bridges)

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📦 Installation

Add to your Cargo.toml:

[dependencies]
agentic-robotics-core = "0.1"
tokio = { version = "1", features = ["full"] }
serde = { version = "1", features = ["derive"] }

Or use cargo add:

cargo add agentic-robotics-core
cargo add tokio --features full
cargo add serde --features derive

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🎓 Tutorial: Building Your First Robot Node

Let's build a simple robot system step by step. We'll create a sensor node that publishes data and a controller node that subscribes to it.

Step 1: Create a Sensor Node

use agentic_robotics_core::Node;
use serde::{Serialize, Deserialize};
use tokio::time::{sleep, Duration};

#[derive(Serialize, Deserialize, Debug, Clone)]
struct SensorData {
    temperature: f64,
    pressure: f64,
    timestamp: u64,
}

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // Create a node - this is your robot's identity on the network
    let mut node = Node::new("sensor_node")?;

    // Create a publisher - this broadcasts sensor data
    let publisher = node.publish::<SensorData>("/sensors/environment")?;

    println!("🤖 Sensor node started!");

    // Simulate sensor readings at 10 Hz
    for i in 0.. {
        let data = SensorData {
            temperature: 20.0 + (i as f64 * 0.1).sin() * 5.0,  // Simulated
            pressure: 1013.0 + (i as f64 * 0.2).cos() * 10.0,
            timestamp: i,
        };

        publisher.publish(&data).await?;
        println!("📡 Published: temp={:.1}°C, pressure={:.1}hPa",
                 data.temperature, data.pressure);

        sleep(Duration::from_millis(100)).await;  // 10 Hz
    }

    Ok(())
}

What's happening here?

1. Node creation - Node::new() registers your robot component on the network
2. Publisher - publish::<T>() creates a typed channel that can broadcast messages
3. Message type - SensorData is your custom message (any Rust struct with Serialize)
4. Publishing - publish().await sends the message to all subscribers

Step 2: Create a Controller Node

use agentic_robotics_core::Node;
use serde::{Serialize, Deserialize};

#[derive(Serialize, Deserialize, Debug)]
struct SensorData {
    temperature: f64,
    pressure: f64,
    timestamp: u64,
}

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let mut node = Node::new("controller_node")?;

    // Create a subscriber - this receives sensor data
    let subscriber = node.subscribe::<SensorData>("/sensors/environment")?;

    println!("🤖 Controller node started, waiting for sensor data...");

    // Process incoming sensor data
    while let Some(data) = subscriber.recv().await {
        println!("📥 Received: temp={:.1}°C, pressure={:.1}hPa at t={}",
                 data.temperature, data.pressure, data.timestamp);

        // Make control decisions based on sensor data
        if data.temperature > 25.0 {
            println!("🌡️  High temperature detected! Activating cooling...");
        }

        if data.pressure < 1000.0 {
            println!("🌪️  Low pressure warning!");
        }
    }

    Ok(())
}

What's happening here?

1. Subscriber - subscribe::<T>() creates a receiver for a specific topic
2. Receiving - recv().await blocks until a message arrives
3. Type safety - The message is automatically deserialized to SensorData
4. Control logic - You can make decisions based on sensor readings

Step 3: Running Multiple Nodes

Open two terminals:

# Terminal 1: Run sensor node
cargo run --bin sensor_node

# Terminal 2: Run controller node
cargo run --bin controller_node

You'll see:

• Sensor node publishing data at 10 Hz
• Controller node receiving and processing that data
• Automatic discovery - nodes find each other via Zenoh
• Type-safe communication - compile-time guarantees

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🎯 Real-World Use Cases

Use Case 1: Autonomous Vehicle Sensor Fusion

use agentic_robotics_core::Node;
use serde::{Serialize, Deserialize};

#[derive(Serialize, Deserialize, Clone)]
struct LidarScan {
    points: Vec<[f32; 3]>,  // 3D points
    timestamp: u64,
}

#[derive(Serialize, Deserialize, Clone)]
struct CameraImage {
    width: u32,
    height: u32,
    data: Vec<u8>,
}

#[derive(Serialize, Deserialize)]
struct FusedData {
    obstacles: Vec<Obstacle>,
    drivable_area: Vec<[f32; 2]>,
}

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let mut node = Node::new("sensor_fusion")?;

    // Subscribe to multiple sensors
    let lidar_sub = node.subscribe::<LidarScan>("/lidar/scan")?;
    let camera_sub = node.subscribe::<CameraImage>("/camera/image")?;

    // Publish fused data
    let fused_pub = node.publish::<FusedData>("/perception/fused")?;

    // Real-time fusion at 30 Hz
    tokio::spawn(async move {
        loop {
            // Try to get latest data (non-blocking)
            if let Some(lidar) = lidar_sub.try_recv() {
                if let Some(image) = camera_sub.try_recv() {
                    // Fuse lidar + camera data
                    let fused = fuse_sensors(&lidar, &image);
                    fused_pub.publish(&fused).await.ok();
                }
            }
            tokio::time::sleep(Duration::from_millis(33)).await;  // 30 Hz
        }
    });

    Ok(())
}

Performance: With agentic-robotics, you can fuse 100Hz lidar + 30Hz camera with < 1ms latency. In ROS2, you'd struggle with 10Hz.

Use Case 2: Industrial Robot Control

use agentic_robotics_core::Node;
use serde::{Serialize, Deserialize};

#[derive(Serialize, Deserialize, Clone)]
struct JointState {
    positions: [f64; 6],  // 6-DOF robot arm
    velocities: [f64; 6],
    efforts: [f64; 6],
}

#[derive(Serialize, Deserialize)]
struct JointCommand {
    positions: [f64; 6],
    velocities: [f64; 6],
}

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let mut node = Node::new("robot_controller")?;

    let state_sub = node.subscribe::<JointState>("/joint_states")?;
    let cmd_pub = node.publish::<JointCommand>("/joint_commands")?;

    // High-frequency control loop (1 kHz!)
    loop {
        if let Some(state) = state_sub.try_recv() {
            // Compute control law (PID, impedance, etc.)
            let command = compute_control(&state);
            cmd_pub.publish(&command).await?;
        }

        tokio::time::sleep(Duration::from_micros(1000)).await;  // 1 kHz
    }
}

Performance: 1kHz control loops are trivial with agentic-robotics. ROS2 struggles past 100Hz.

Use Case 3: Multi-Robot Coordination

use agentic_robotics_core::Node;
use serde::{Serialize, Deserialize};

#[derive(Serialize, Deserialize, Clone)]
struct RobotPose {
    id: String,
    x: f64,
    y: f64,
    theta: f64,
}

#[derive(Serialize, Deserialize)]
struct TeamCommand {
    formation: String,  // "line", "circle", "wedge"
    target: (f64, f64),
}

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let robot_id = "robot_1";
    let mut node = Node::new(&format!("robot_{}", robot_id))?;

    // Publish own pose
    let pose_pub = node.publish::<RobotPose>("/team/poses")?;

    // Subscribe to all team poses
    let poses_sub = node.subscribe::<RobotPose>("/team/poses")?;

    // Subscribe to team commands
    let cmd_sub = node.subscribe::<TeamCommand>("/team/command")?;

    // Coordinate with team
    tokio::spawn(async move {
        let mut team_poses = Vec::new();

        loop {
            // Collect team poses
            while let Some(pose) = poses_sub.try_recv() {
                if pose.id != robot_id {
                    team_poses.push(pose);
                }
            }

            // Execute team command
            if let Some(cmd) = cmd_sub.try_recv() {
                let my_target = compute_formation_position(
                    &cmd.formation,
                    robot_id,
                    &team_poses
                );
                println!("Moving to formation position: {:?}", my_target);
            }

            tokio::time::sleep(Duration::from_millis(100)).await;
        }
    });

    Ok(())
}

Performance: Coordinate 100+ robots with millisecond latency. ROS2 starts having issues past 10 robots.

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🔧 Advanced Features

1. Custom Message Types (Any Rust Struct!)

use serde::{Serialize, Deserialize};

// Simple message
#[derive(Serialize, Deserialize)]
struct Position {
    x: f64,
    y: f64,
    z: f64,
}

// Complex message with nested types
#[derive(Serialize, Deserialize)]
struct RobotState {
    pose: Pose,
    velocity: Twist,
    sensors: SensorArray,
    metadata: HashMap<String, String>,
}

// Just add Serialize + Deserialize - that's it!

2. Multiple Serialization Formats

use agentic_robotics_core::serialization::*;

// CDR (ROS2-compatible, fast)
let bytes = serialize_cdr(&robot_state)?;
let recovered: RobotState = deserialize_cdr(&bytes)?;

// JSON (human-readable, debugging)
let json = serialize_json(&robot_state)?;
println!("State: {}", json);

// rkyv (zero-copy, ultra-fast)
let archived = serialize_rkyv(&robot_state)?;

3. Topic Discovery and Introspection

// List all active topics
let topics = node.list_topics()?;
for topic in topics {
    println!("Topic: {} (type: {})", topic.name, topic.type_name);
}

// Get topic statistics
let stats = node.topic_stats("/sensor/data")?;
println!("Messages/sec: {}", stats.rate);
println!("Bandwidth: {} KB/s", stats.bandwidth / 1024);

4. Quality of Service (QoS) Configuration

use agentic_robotics_core::{QoS, Reliability, Durability};

// Reliable delivery (guaranteed, ordered)
let qos = QoS {
    reliability: Reliability::Reliable,
    durability: Durability::Transient,  // Late joiners get history
    history_depth: 10,
};

let pub_important = node.publish_with_qos::<Command>("/critical_commands", qos)?;

// Best-effort (fast, lossy OK)
let qos_fast = QoS {
    reliability: Reliability::BestEffort,
    durability: Durability::Volatile,
    history_depth: 1,
};

let pub_sensor = node.publish_with_qos::<SensorData>("/sensors/raw", qos_fast)?;

5. Non-Blocking Reception

// Blocking (waits for message)
let msg = subscriber.recv().await;  // Waits indefinitely

// Non-blocking (returns immediately)
if let Some(msg) = subscriber.try_recv() {
    // Process message
} else {
    // No message available, do something else
}

// Timeout
use tokio::time::timeout;

match timeout(Duration::from_millis(100), subscriber.recv()).await {
    Ok(Some(msg)) => println!("Got message: {:?}", msg),
    Ok(None) => println!("Channel closed"),
    Err(_) => println!("Timeout - no message in 100ms"),
}

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🌉 Bridging with ROS2

You can run agentic-robotics and ROS2 nodes side-by-side:

Option 1: Use DDS Backend (Native ROS2 Compatibility)

use agentic_robotics_core::{Node, Middleware};

// Use DDS/RTPS (ROS2's protocol)
let mut node = Node::with_middleware("robot", Middleware::Dds)?;

// Now fully compatible with ROS2 nodes!
let pub = node.publish::<String>("/status")?;

From ROS2:

ros2 topic echo /status

Option 2: Use Zenoh with ROS2 Bridge

# Terminal 1: Your agentic-robotics node
cargo run --release

# Terminal 2: Zenoh-ROS2 bridge
zenoh-bridge-ros2

# Terminal 3: ROS2 nodes work normally
ros2 topic list
ros2 topic echo /sensor/data

Migration from ROS2: Side-by-Side Comparison

ROS2 (C++)	Agentic Robotics (Rust)
rclcpp::Node::make_shared("node")	Node::new("node")?
create_publisher<T>(topic, qos)	publish::<T>(topic)?
create_subscription<T>(topic, qos, callback)	subscribe::<T>(topic)?
publisher->publish(msg)	pub.publish(&msg).await?
rclcpp::spin(node)	loop { sub.recv().await }

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🐛 Troubleshooting

Problem: "No such file or directory" when creating a node

Solution: Make sure Zenoh is configured correctly. By default, nodes discover each other automatically on localhost.

// Explicit configuration (optional)
let config = NodeConfig {
    discovery: Discovery::Multicast,  // or Discovery::Unicast(peers)
    ..Default::default()
};
let node = Node::with_config("robot", config)?;

Problem: Messages not being received

Check:

1. Topic names match exactly (including leading /)
2. Message types match on publisher and subscriber
3. Both nodes are running
4. Firewall isn't blocking UDP multicast (port 7447)

// Debug: Print when messages are published
pub.publish(&msg).await?;
println!("✅ Published to /sensor/data");

// Debug: Check if subscriber is connected
if subscriber.is_connected() {
    println!("📡 Subscriber connected");
} else {
    println!("❌ No publisher found for /sensor/data");
}

Problem: High latency or low throughput

Solutions:

1. Use try_recv() instead of recv().await in hot loops
2. Pre-allocate message buffers
3. Use BestEffort QoS for sensor data
4. Consider message batching for high-frequency data

// BAD: Allocates every time
loop {
    let msg = SensorData { data: vec![0; 1000] };
    pub.publish(&msg).await?;
}

// GOOD: Reuse allocation
let mut msg = SensorData { data: vec![0; 1000] };
loop {
    update_sensor_data(&mut msg.data);
    pub.publish(&msg).await?;
}

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📊 Performance Tuning

1. Use Release Builds

cargo build --release  # 10-100x faster than debug!

2. Profile Your Code

cargo install flamegraph
cargo flamegraph --bin my_robot

3. Optimize Critical Paths

// Use try_recv() in control loops (non-blocking)
loop {
    if let Some(sensor) = sensor_sub.try_recv() {
        let control = compute_control(&sensor);  // Expensive
        cmd_pub.publish(&control).await?;
    }
    tokio::time::sleep(Duration::from_micros(1000)).await;
}

// Use channels for CPU-bound work
let (tx, mut rx) = tokio::sync::mpsc::channel(100);
tokio::spawn(async move {
    while let Some(data) = rx.recv().await {
        // Process in background
        let result = expensive_computation(data);
        result_pub.publish(&result).await.ok();
    }
});

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🧪 Testing

#[cfg(test)]
mod tests {
    use super::*;

    #[tokio::test]
    async fn test_pub_sub() {
        let mut node = Node::new("test_node").unwrap();
        let pub = node.publish::<String>("/test").unwrap();
        let sub = node.subscribe::<String>("/test").unwrap();

        // Publish
        pub.publish(&"Hello".to_string()).await.unwrap();

        // Receive
        let msg = sub.recv().await.unwrap();
        assert_eq!(msg, "Hello");
    }
}

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📚 Examples

Complete working examples in the repository:

• 01-hello-robot.ts - Basic pub/sub (10s)
• 02-autonomous-navigator.ts - A* pathfinding with obstacle avoidance (30s)
• 03-multi-robot-coordinator.ts - Multi-robot task allocation (30s)
• 04-swarm-intelligence.ts - 15-robot emergent behavior (60s)
• 05-robotic-arm-manipulation.ts - 6-DOF inverse kinematics (40s)
• 06-vision-tracking.ts - Kalman filtering and object tracking (30s)
• 07-behavior-tree.ts - Hierarchical reactive control (30s)
• 08-adaptive-learning.ts - Experience-based learning (25s)

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🤝 Contributing

We welcome contributions! See CONTRIBUTING.md.

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📄 License

Licensed under either of:

• Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
• MIT License (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

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🔗 Links

• Homepage: ruv.io
• Documentation: docs.rs/agentic-robotics-core
• Repository: github.com/ruvnet/vibecast
• Performance Report: PERFORMANCE_REPORT.md
• Optimization Guide: OPTIMIZATIONS.md
• Examples: examples/

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