Autonomous Swarm Urban Car Search: First 30 Minutes Developer Wiki

Pages

1. Start Here: System Mental Model & 30-Minute Reading OrderCore mental model for the decentralized multi-robot car search system, team subsystem boundaries between Swarm and SLAM, essential glossary terminology, and the recommended code-reading order.
2. First Execution, Scenarios & Runtime BoundariesHands-on guide to launching deterministic simulation scenarios (A through F), inspecting generated visual artifacts (ASCII HUD, SVG snapshots, Matplotlib panels), and understanding environment setup constraints and dependencies.
3. ACO Multi-Objective Scoring & Tri-Layer StigmergyDetailed mechanics of the decentralized Ant Colony Optimization engine, the 8-factor score formulation, Boltzmann Softmax action selection, tri-layer pheromone evaporation dynamics, and recursive Bayesian target probability updates.
4. Perception Pipeline & Subsystem ContractsThe 5-stage target identification pipeline covering raycast FOV occlusion, Levenshtein fuzzy license plate OCR, appearance verification, temporal tracking, and the abstract ISLAMProvider interface contract decoupling Swarm from SLAM.
5. Autonomous Fault Detection & Dynamic ReallocationTelemetry monitoring for silent heartbeat timeouts, battery exhaustion, and kinematic stalls, coupled with dynamic task revocation, avoidance pheromone deposition over disabled units, and immediate peer reallocation.
6. Beyond the First 30 Minutes: 3D Gazebo & Extension PointsSynthesis of initial learnings, bridging from 2D discrete simulation to containerized ROS 2 / Gazebo Fortress 3D worlds, running Monte Carlo benchmark evaluations against baselines, and architectural extension hooks.