Engineering intelligence for autonomous systems
A structured technical library spanning the estimation, decision, and control layers that make autonomous platforms work.
Trajectory generation and command logic
Guidance laws, path following, intercept geometry, waypoint management, terminal guidance, trajectory optimization, and the interface between planning and control.
Stability and closed-loop response
PID control, state-space methods, observers, LQR, model predictive control, robust control, actuator dynamics, and practical tuning tradeoffs.
Perception, planning, and decision systems
Behavior planning, obstacle avoidance, sensor-driven decision logic, autonomy stacks, verification, and the boundary between deterministic control and higher-level intelligence.
Architecture and integration
Timing, coordinate frames, interfaces, compute constraints, redundancy, fault handling, hardware-in-the-loop testing, and the integration details that often determine field performance.
Need a system-level view?
See how these disciplines combine across aerospace, robotics, autonomous vehicles, maritime systems, and defense platforms.