MichaelGrupp/evo

Features

• SLAM and Odometry - Provides a comprehensive framework for measuring the precision and accumulated drift of SLAM and odometry systems.
• Analysis Libraries - Serves as a specialized library for measuring drift and precision in robot odometry by comparing estimated paths against ground truth.
• Trajectory Accuracy Evaluation - Quantifies localization precision by computing absolute and relative pose errors (ATE and RPE) against ground truth.
• Ground Truth Comparisons - Calculates absolute and relative pose errors by comparing estimated trajectories against recorded ground-truth data.
• Trajectory Error Quantification - Compare estimated poses against a reference to evaluate global consistency and the overall accuracy of a trajectory.
• Robotics Format Importers - Ships a modular input system with dedicated drivers to parse diverse robotics trajectory standards and ROS bagfiles.
• Spatial Trajectory Plotting - Renders high-performance 2D and 3D spatial views of poses and coordinates for trajectory analysis.
• Affine Matrix Transformations - Applies 3x3 or 4x4 affine matrices to map and shift coordinates for 3D translation and rotation.
• Evaluation Tools - Provides a framework for calculating absolute and relative pose errors to quantify SLAM algorithm accuracy.
• Trajectory Visualizers - Plots trajectory poses in 2D or 3D views and generates charts for coordinates, angles, and velocities.
• Evaluation Frameworks - Provides tools to quantify SLAM accuracy by computing absolute and relative pose errors against ground truth.
• Relative Pose Error Metrics - Compare the difference between consecutive or overlapping pose deltas to track local accuracy and drift over time.
• Coordinate Frame Transformations - Implements a pipeline for applying rotation and translation matrices to shift trajectory data between local and global spatial frames.
• Trajectory Alignment Tools - Provides algorithms to transform and align estimated trajectories with ground truth for direct geometric comparison.
• Trajectory Error Quantification - Quantifies trajectory accuracy by computing root mean square error and median translation differences against ground truth.
• Planar Pose Projections - Flattens 3D trajectory poses into specified 2D planes such as xy, xz, or yz for simplified analysis.
• Robotic Trajectory Standardizers - Reads trajectory and ground truth data from common robotics dataset standards for subsequent evaluation.
• Processing Utilities - Offers utilities for importing, filtering, and aligning trajectory data from ROS bagfiles and other industry-standard formats.
• ROS Libraries and Tools - Provides utilities for extracting and processing trajectory information from ROS bagfiles for motion evaluation.
• Temporal Stream Synchronization - Implements a time-series alignment mechanism to synchronize multiple trajectories by applying constant temporal offsets.
• ROS Bag Trajectory Extraction - Extracts trajectory data from ROS bagfiles including the ability to perform transform lookups between frames.
• Planar Pose Projections - Provides a visualization mechanism that flattens 3D spatial pose data onto specific 2D planes.
• Geographic Tile Overlays - Visualizes trajectories on real-world maps by overlaying geo-referenced tiles from external providers.
• Trajectory Pose Transformations - Transforms trajectory poses using custom 3D rotation and translation matrices applied from global or local frames.
• Experiment Result Comparators - Aggregates and contrasts performance metrics from multiple evaluation runs to compare trajectory accuracy.
• Temporal Trajectory Synchronization - Ensures temporal alignment between multiple trajectories by matching timestamps and applying constant offsets.
• Map Data Overlays - Inserts 2D ROS map images as custom data layers on top of trajectory plots for environmental context.
• Localization and State Estimation - Python package for evaluating odometry and SLAM.
• Evaluation Tools - Command-line tools for evaluating trajectory and pose estimation accuracy.

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