Workspace Analyzer Visualizers

Workspace Analyzer Visualizers#

The visualizers module provides visualization tools for analyzing robotic workspace data in 3D space.

Table of Contents#

Overview#

The visualizers module enables:

  • Workspace reachability visualization with multiple rendering styles

  • 3D point cloud, voxel, sphere, and coordinate axis representations

  • Multiple backends: Open3D, Matplotlib, and simulation environments

  • Factory pattern for easy visualizer creation

Visualization Types#

1. Point Cloud Visualizer ✅#

Fast rendering for large datasets.

from embodichain.lab.sim.utility.workspace_analyzer.visualizers import PointCloudVisualizer

visualizer = PointCloudVisualizer(backend='open3d', point_size=2.0)

Best for: Large point sets (>10k points), fast rendering

2. Voxel Visualizer ✅#

Volumetric representation for occupancy maps.

from embodichain.lab.sim.utility.workspace_analyzer.visualizers import VoxelVisualizer

visualizer = VoxelVisualizer(backend='open3d', voxel_size=0.01)

Best for: Occupancy grids, collision detection

3. Sphere Visualizer ✅#

Smooth visualization for reachability zones.

from embodichain.lab.sim.utility.workspace_analyzer.visualizers import SphereVisualizer

visualizer = SphereVisualizer(backend='open3d', sphere_radius=0.005)

Best for: Publication-quality figures, smooth appearance

4. Axis Visualizer ✅#

Coordinate frame visualization for poses and transformations.

from embodichain.lab.sim.utility.workspace_analyzer.visualizers import AxisVisualizer

visualizer = AxisVisualizer(backend='sim_manager', sim_manager=sim, axis_length=0.15)

Best for: Robot poses, end-effector frames, coordinate system visualization

Usage Examples#

Basic Usage#

import numpy as np
from embodichain.lab.sim.utility.workspace_analyzer.visualizers import create_visualizer

# Generate workspace data
points = np.random.rand(1000, 3) * 2 - 1  # Random points in [-1, 1]³
colors = np.random.rand(1000, 3)  # Random colors

# Create and use visualizer
visualizer = create_visualizer('point_cloud', backend='open3d', point_size=3.0)
result = visualizer.visualize(points, colors)
visualizer.show()

Factory Pattern#

from embodichain.lab.sim.utility.workspace_analyzer.visualizers import VisualizerFactory

factory = VisualizerFactory()
visualizer = factory.create_visualizer('voxel', backend='open3d', voxel_size=0.02)

# Create axis visualizer
axis_viz = factory.create_visualizer('axis', backend='sim_manager', sim_manager=sim)

Backend Support#

Available Backends#

  • open3d: Interactive 3D visualization (requires pip install open3d)

  • matplotlib: Static figures and plots (requires pip install matplotlib)

  • sim_manager: Integration with simulation environment

  • data: Returns processed data without visualization (headless mode)

Quick Reference#

Available Visualizers:

  • PointCloudVisualizer: Fast rendering for large datasets

  • VoxelVisualizer: Volumetric representation for occupancy maps

  • SphereVisualizer: Smooth visualization for publication figures

  • AxisVisualizer: Coordinate frame visualization for poses

Common Parameters:

  • PointCloud: backend, point_size

  • Voxel: backend, voxel_size

  • Sphere: backend, sphere_radius, sphere_resolution

  • Axis: backend, axis_length, axis_size, sim_manager

Quick Creation:

from embodichain.lab.sim.utility.workspace_analyzer.visualizers import create_visualizer
import numpy as np

# Create any visualizer
visualizer = create_visualizer('point_cloud', backend='open3d', point_size=2.0)
visualizer = create_visualizer('voxel', backend='open3d', voxel_size=0.01)
visualizer = create_visualizer('sphere', backend='open3d', sphere_radius=0.005)

# Create axis visualizer for coordinate frames
axis_viz = create_visualizer('axis', backend='sim_manager', sim_manager=sim, axis_length=0.05)

# Visualize coordinate frame at robot end-effector
pose = np.eye(4)
pose[:3, 3] = [1.0, 0.5, 1.2]  # Set position
axis_viz.visualize(pose, name_prefix="end_effector_frame")
axis_viz.show()
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