Defining Tree

After introducing the execution model, the next step is to define a concrete tree in code and execute it.

As this is a 🐝 tree let’s model one of its behaviors.

Root
└── Sequence
    ├── DetectFlower
    ├── FlyTo
    └── CollectPollen

In code, this can be written as:

// Some parts of boilerplate code has been hidden, if you want to see all click 
// Show hidden lines in the top right corner of the box

// This is only needed by mdbook to link the crates
extern crate tokio;
extern crate anyhow;
extern crate beetry;
use std::time::Duration;
use anyhow::{Result, anyhow};
use beetry::{
    leaf::{ActionBehavior, ActionTask, Task},
    node::{BoxNode, Root, MemorySequence},
    runtime::{PeriodicTick, PeriodicTicker, TickStatus, Tree, TreeEngine, TreeEngineConfig},
};
use tokio::sync::mpsc;
#[derive(Debug, Clone)]
struct Pose {
    x: f32,
    y: f32,
    z: f32,
}

struct DetectFlower {
    send: mpsc::Sender<Pose>,
}

impl ActionBehavior for DetectFlower {
    fn task(&mut self) -> Result<ActionTask> {
        Ok(ActionTask::new(DetectFlowerTask {
            send: self.send.clone(),
        }))
    }
}

struct DetectFlowerTask {
    send: mpsc::Sender<Pose>,
}

impl Task for DetectFlowerTask {
    async fn run(self) -> TickStatus {
        // detect flower dummy implementation
        if self
            .send
            .try_send(Pose {
                x: 1.3,
                y: 2.1,
                z: 0.7,
            })
            .is_err()
        {
            return TickStatus::Failure;
        }
        TickStatus::Success
    }
}

struct FlyTo {
    recv: mpsc::Receiver<Pose>,
}

impl ActionBehavior for FlyTo {
    fn task(&mut self) -> Result<ActionTask> {
        Ok(ActionTask::new(FlyToTask {
            pose: self.recv.try_recv().ok(),
        }))
    }
}

struct FlyToTask {
    pose: Option<Pose>,
}

impl Task for FlyToTask {
    async fn run(self) -> TickStatus {
        // fly to dummy implementation
        let Some(pose) = self.pose else {
            return TickStatus::Failure;
        };
        let _ = (pose.x, pose.y, pose.z);
        TickStatus::Success
    }
}

struct CollectPollen;

impl ActionBehavior for CollectPollen {
    fn task(&mut self) -> Result<ActionTask> {
        Ok(ActionTask::new(CollectPollenTask))
    }
}

struct CollectPollenTask;

impl Task for CollectPollenTask {
    async fn run(self) -> TickStatus {
        TickStatus::Success
    }
}

#[tokio::main]
async fn main() -> Result<()> {
    let engine = TreeEngine::new(TreeEngineConfig::default());
    let (send, recv) = mpsc::channel(1);
    let tree = Tree::new(Root::new(MemorySequence::new([
        Box::new(engine.register_action(DetectFlower { send })) as BoxNode,
        Box::new(engine.register_action(FlyTo { recv })) as BoxNode,
        Box::new(engine.register_action(CollectPollen)) as BoxNode,
    ])));

    let mut engine = engine.tree(tree).start_executor()?;
    let ticker = PeriodicTicker::new(PeriodicTick::new(Duration::from_millis(10)));
    let status = engine.tick_till_terminal(ticker).await?;
    Ok(())
}

The example already covers a lot. It uses ActionBehavior to define custom action logic, Tree to define the hierarchy of nodes, and TreeEngine to register action nodes and execute the tree.

There are a few things worth keeping in mind.

First, Beetry does not force a specific inter-node communication. In this example, a Tokio channel is used to send and receiver Pose, but the same tree could use a blackboard, shared state, or any other IPC-style mechanism if desired.

Second, the shape of the tree is small, so its structure is easy to understand. Adding or removing one or two nodes is not a major problem at this scale. In practical applications, however, trees usually become much wider and deeper. Once that happens, reasoning about their structure in code becomes harder. In practice, trees of realistic size are usually designed in Beehive (see Beehive chapter for more details).

Using Beehive makes it easier to reason about a tree, at the cost of boxing nodes and slightly restricting the constructor API, since arbitrary data cannot be passed directly.