Capabilities

Capability to evidence

Each capability below points to the project that demonstrates it most directly. The detailed pages carry the measurements, implementation boundaries, and validation limits.

Capability Matrix

Capability	What Shows It	Main Evidence
Mathematical modeling	Physical dynamics, coordinate residuals, convergence paths, and explicit numerical diagnostics	ballistic-solver
API and deployability	Modern C++ API, C ABI, Python/PyPI, Unity/C#, Godot, and ARM64 hardware integration	ballistic-solver
ROS 2 / vehicle autonomy integration	FAST-LIO bridge, occupancy mapping, planner integration, measured-delay follower, and Ioniq CAN path	Mapless Autonomous Parking
Visual perception	Metric camera odometry, anchor-map direction/attitude correction, dense occupancy, and CARLA evaluation	Monoscale
Operational robustness	NTRIP handling, serial retry, timeout detection, live monitoring, and remote deployment workflow	Racing Telemetry Stack
Data analysis tooling	Multi-format logs, gate-aligned timing, simulator registration, synchronized media/replay, and report export	Racing Analyze GUI
Open-source collaboration	Reviewed upstream changes with measured impact and backward-compatible defaults	Autoware contributions

Working Principles

• Model the actual bottleneck before choosing the implementation path.
• Make runtime state inspectable through explicit status, logs, plots, replay, or monitoring.
• Package useful cores behind stable APIs, launch paths, services, or analysis workflows.

Evidence Map

• Measured behavior: current solver benchmarks, visual-odometry ablations, telemetry regression tests, research comparisons, and camera-payload measurements.
• Physical validation: real-vehicle parking and a Rock 5B + STM32 solver integration with live vision input.
• Upstream validation: three reviewed and merged Autoware Universe contributions.
• Operational tooling: logs, monitoring, replay, and analysis interfaces that make field behavior inspectable.