Crate ruvector_robotics 

ruvector-robotics

Unified cognitive robotics platform built on ruvector’s vector database, graph neural networks, and self-learning infrastructure.

Modules

• bridge: Core robotics types, converters, spatial indexing, and perception pipeline
• perception: Scene graph construction, obstacle detection, trajectory prediction
• cognitive: Cognitive architecture with behavior trees, memory, skills, and swarm intelligence
• mcp: Model Context Protocol tool registrations for agentic robotics

Quick Start

use ruvector_robotics::bridge::{Point3D, PointCloud, SpatialIndex};

// Create a point cloud from sensor data
let cloud = PointCloud::new(
    vec![Point3D::new(1.0, 2.0, 3.0), Point3D::new(4.0, 5.0, 6.0)],
    1000,
);

// Index and search
let mut index = SpatialIndex::new(3);
index.insert_point_cloud(&cloud);
let nearest = index.search_nearest(&[2.0, 3.0, 4.0], 1).unwrap();
assert_eq!(nearest.len(), 1);

Re-exports

pub use bridge::BridgeConfig;

pub use bridge::DistanceMetric;

pub use bridge::OccupancyGrid;

pub use bridge::Obstacle as BridgeObstacle;

pub use bridge::Point3D;

pub use bridge::PointCloud;

pub use bridge::Pose;

pub use bridge::Quaternion;

pub use bridge::RobotState;

pub use bridge::SceneEdge;

pub use bridge::SceneGraph;

pub use bridge::SceneObject;

pub use bridge::SensorFrame;

pub use bridge::SpatialIndex;

pub use bridge::Trajectory;

pub use cognitive::BehaviorNode;

pub use cognitive::BehaviorStatus;

pub use cognitive::BehaviorTree;

pub use cognitive::CognitiveCore;

pub use cognitive::CognitiveState;

pub use perception::ObstacleDetector;

pub use perception::PerceptionConfig;

pub use perception::PerceptionPipeline;

pub use perception::SceneGraphBuilder;

pub use planning::GridPath;

pub use planning::VelocityCommand;

Modules

bridge

Core robotics types, converters, spatial indexing, and perception pipeline.

cognitive

Cognitive architecture for autonomous robot behavior.

mcp

MCP tool registrations for agentic robotics.

perception

Perception subsystem: scene graph construction, obstacle detection, and pipeline.

planning

Motion planning: A* grid search and potential-field velocity commands.