Squashed 'vendor/ruvector/' content from commit b64c2172

git-subtree-dir: vendor/ruvector
git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900

crates/ruvector-robotics/examples/obstacle_detection.rs

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+//! Example: obstacle detection from point cloud data.
+//!
+//! Demonstrates:
+//! - Creating a `PointCloud` from synthetic sensor data
+//! - Running the `ObstacleDetector` to find clusters
+//! - Classifying obstacles as Static, Dynamic, or Unknown
+
+use ruvector_robotics::bridge::{Point3D, PointCloud};
+use ruvector_robotics::perception::{ObstacleDetector, ObstacleClass};
+use ruvector_robotics::perception::config::ObstacleConfig;
+
+fn main() {
+    println!("=== Obstacle Detection Demo ===\n");
+
+    // Simulate a warehouse scene.
+    let mut points = Vec::new();
+
+    // Wall (static, elongated)
+    for i in 0..30 {
+        points.push(Point3D::new(5.0, i as f32 * 0.3, 0.0));
+        points.push(Point3D::new(5.1, i as f32 * 0.3, 0.0));
+    }
+
+    // Moving person (dynamic, compact)
+    for dx in 0..4 {
+        for dy in 0..4 {
+            points.push(Point3D::new(
+                2.0 + dx as f32 * 0.15,
+                3.0 + dy as f32 * 0.15,
+                0.0,
+            ));
+        }
+    }
+
+    // Small debris (may be below threshold)
+    points.push(Point3D::new(8.0, 1.0, 0.0));
+    points.push(Point3D::new(8.1, 1.0, 0.0));
+
+    let cloud = PointCloud::new(points, 1_000_000);
+    let robot_pos = [0.0, 0.0, 0.0];
+
+    println!("Point cloud: {} points", cloud.len());
+    println!("Robot position: {:?}\n", robot_pos);
+
+    let config = ObstacleConfig {
+        min_obstacle_size: 3,
+        max_detection_range: 30.0,
+        safety_margin: 0.5,
+    };
+    let detector = ObstacleDetector::new(config);
+
+    // Detect
+    let obstacles = detector.detect(&cloud, &robot_pos);
+    println!("Detected {} obstacle clusters:\n", obstacles.len());
+
+    for (i, obs) in obstacles.iter().enumerate() {
+        println!(
+            "  Obstacle {}: center=[{:.2}, {:.2}, {:.2}], extent=[{:.2}, {:.2}, {:.2}], points={}, dist={:.2}m",
+            i, obs.center[0], obs.center[1], obs.center[2],
+            obs.extent[0], obs.extent[1], obs.extent[2],
+            obs.point_count, obs.min_distance,
+        );
+    }
+
+    // Classify
+    let classified = detector.classify_obstacles(&obstacles);
+    println!("\nClassification:");
+    for (i, c) in classified.iter().enumerate() {
+        let label = match c.class {
+            ObstacleClass::Static => "STATIC (wall/barrier)",
+            ObstacleClass::Dynamic => "DYNAMIC (movable)",
+            ObstacleClass::Unknown => "UNKNOWN",
+        };
+        println!(
+            "  Obstacle {}: {} (confidence: {:.2})",
+            i, label, c.confidence
+        );
+    }
+}