Robotics MCP Server

"""Mock data fixtures for testing without hardware.""" import random from typing import Any, Dict, List import numpy as np def mock_lidar_scan(num_points: int = 360, range_min: float = 0.1, range_max: float = 12.0) -> Dict[str, Any]: """Generate mock LiDAR scan data. Args: num_points: Number of scan points. range_min: Minimum range in meters. range_max: Maximum range in meters. Returns: Mock LiDAR scan data. """ angles = np.linspace(0, 2 * np.pi, num_points) ranges = np.random.uniform(range_min, range_max, num_points) # Add some obstacles (closer ranges) obstacle_indices = random.sample(range(num_points), num_points // 10) for idx in obstacle_indices: ranges[idx] = random.uniform(range_min, 2.0) return { "ranges": ranges.tolist(), "angles": angles.tolist(), "intensities": np.random.uniform(0, 1, num_points).tolist(), "range_min": range_min, "range_max": range_max, "timestamp": 0.0, } def mock_robot_status(robot_id: str, robot_type: str = "scout") -> Dict[str, Any]: """Generate mock robot status. Args: robot_id: Robot identifier. robot_type: Type of robot. Returns: Mock robot status. """ return { "robot_id": robot_id, "robot_type": robot_type, "battery_level": random.uniform(0.5, 1.0), "position": {"x": random.uniform(-5, 5), "y": random.uniform(-5, 5), "theta": random.uniform(0, 2 * np.pi)}, "velocity": {"linear": random.uniform(0, 0.3), "angular": random.uniform(-2, 2)}, "connected": True, "status": "idle", } def mock_sensor_data() -> Dict[str, Any]: """Generate mock sensor data. Returns: Mock sensor data. """ return { "tof": {"distance": random.uniform(0.1, 3.0), "valid": True}, "imu": { "orientation": {"x": 0.0, "y": 0.0, "z": 0.0, "w": 1.0}, "angular_velocity": {"x": 0.0, "y": 0.0, "z": 0.0}, "linear_acceleration": {"x": 0.0, "y": 0.0, "z": 9.8}, }, "light": {"ch0": random.randint(0, 65535), "ch1": random.randint(0, 65535)}, } def mock_map_data(width: int = 100, height: int = 100, resolution: float = 0.05) -> Dict[str, Any]: """Generate mock occupancy grid map. Args: width: Map width in pixels. height: Map height in pixels. resolution: Map resolution in meters per pixel. Returns: Mock map data. """ # Create a simple map with walls around edges and some obstacles grid = np.ones((height, width), dtype=np.int8) * -1 # Unknown # Walls around edges grid[0, :] = 100 # Occupied grid[-1, :] = 100 grid[:, 0] = 100 grid[:, -1] = 100 # Some obstacles for _ in range(5): x = random.randint(10, width - 10) y = random.randint(10, height - 10) size = random.randint(3, 8) grid[y - size : y + size, x - size : x + size] = 100 # Free space grid[10:-10, 10:-10] = 0 return { "width": width, "height": height, "resolution": resolution, "origin": {"x": -width * resolution / 2, "y": -height * resolution / 2, "theta": 0.0}, "data": grid.tolist(), }