Pywayne Vio Tools

Pywayne VIO Tools

Overview

Provides utilities for VIO data processing: convert between SE(3) transformation matrices and pose representations, and visualize pose trajectories in 3D with orientation indicators.

Quick Start

from pywayne.vio.tools import SE3_to_pose, pose_to_SE3, visualize_pose
import numpy as np

# Convert SE(3) to pose
SE3 = np.eye(4)  # Single 4x4 SE(3) matrix
pose = SE3_to_pose(SE3)  # Returns [tx, ty, tz, qw, qx, qy, qz]

# Batch conversion
SE3_array = np.random.randn(10, 4, 4)  # 10 SE(3) matrices
poses = SE3_to_pose(SE3_array)

# Convert back to SE(3)
SE3_recon = pose_to_SE3(pose)

# Visualize poses
visualize_pose(poses)  # 3D plot with position markers and orientation arrows

Core Functions

SE3_to_pose

Convert SE(3) transformation matrices to pose representation.

Input: SE3_mat - Single 4x4 SE(3) matrix or array of N SE(3) matrices shape (N, 4, 4)

Output: pose - Array shape (1, 7) or (N, 7) containing [tx, ty, tz, qw, qx, qy, qz]. A single input preserves the historical length-1 batch dimension.

Dependencies: qmt.quatFromRotMat() for quaternion extraction

pose_to_SE3

Convert pose representation back to SE(3) transformation matrices.

Input: pose_mat - Single pose shape (7,) or array of N poses shape (N, 7) with [tx, ty, tz, qw, qx, qy, qz]

Output: SE3_mat - Array of SE(3) matrices shape (1, 4, 4) or (N, 4, 4). A single input preserves the historical length-1 batch dimension.

Dependencies: qmt.quatToRotMat(), ahrs.Quaternion

visualize_pose

3D visualization of SE(3) poses with position markers and orientation arrows.

Parameters:

• poses: Array of poses [tx, ty, tz, qw, qx, qy, qz]
• arrow_length_ratio: Scale factor for orientation arrows (default: 0.1)

Visualization:

• Black dots: Position (translation)
• Red arrow: X-axis orientation
• Green arrow: Y-axis orientation
• Blue arrow: Z-axis orientation

Dependencies: matplotlib.pyplot, qmt.quatToRotMat()

Data Formats

SE(3) Matrix

[[R00 R01 R02 tx]
 [R10 R11 R12 ty]
 [R20 R21 R22 tz]
 [  0   0   0  1]]

Pose Representation

[tx, ty, tz, qw, qx, qy, qz]

Translation: tx, ty, tz (meters) Quaternion: qw, qx, qy, qz (Hamilton convention)

Dependencies

Required packages:

• numpy - Array operations
• qmt - Quaternion utilities
• ahrs - Quaternion class
• matplotlib - 3D visualization

Install with:

pip install numpy qmt ahrs matplotlib