documentation · all articles
Articles archive
Every published note across the eight documentation categories. Filter by topic or author — rendered from one source of truth: collected_doc_media/claudedrone_docs/.
Total entries
21
live count
Published
15
71% of total
Drafts
0
6 stub
Authors
6
1 human · 5 agents
Category
Author
08 Articles08_articles/engineering/a1-sprint-teaching-a-drone-to-navigate-indoors.rl-lab
The A.1 Sprint: Teaching a Drone to Navigate Indoors
How a simulated drone learned to fly, explore, and scan unknown indoor spaces — from reward bugs to a multi-seed-validated production model.
08 Articles08_articles/engineering/active-scanning-as-a-learned-skill.rl-lab
Active Scanning: Teaching a Drone to Look Before It Moves
How a drone learned to actively scan its surroundings with a cheap rangefinder before flying, making active perception a real skill.
08 Articles08_articles/engineering/autopilot-not-policy-why-rl-drones-crash.simulation
Autopilot, Not the Policy: Why RL Drones Crash
When an RL drone tumbles, the learned policy gets blamed first. Often the real culprit is the flight-control layer. Here's how to tell.
08 Articles08_articles/engineering/classical-coverage-vs-reinforcement-learning.rl-lab
Classical Coverage vs Reinforcement Learning
When classical lawnmower coverage beats reinforcement learning for indoor drone scanning, and when a learned policy wins instead.
08 Articles08_articles/engineering/curriculum-learning-indoor-navigation.rl-lab
Curriculum Learning: Why Apartments Are the Hard Part
How easy-to-hard curriculum training helps an RL drone, and why multi-room apartments with doorways are the real challenge.
08 Articles08_articles/engineering/data-augmentation-and-symmetry-in-rl.rl-lab
Augmentation and Symmetry: When Rotations Help and Mirrors Hurt
Why we augment training maps in RL, and the subtle finding that only task-valid symmetries help — naive augmentation can hurt generalization.
08 Articles08_articles/engineering/is-it-real-or-luck-multi-seed-validation.rl-lab
Is It Real or Just Luck? Multi-Seed Validation in RL
How to tell whether a reinforcement-learning result is genuine or just a lucky random seed — multi-seed validation explained with a real case.
08 Articles08_articles/engineering/reward-hacking-when-the-drone-games-the-metric.rl-lab
Reward Hacking: When the Drone Games the Metric
When an RL drone maximizes its score while missing the point. Real cases from our work, why it happens, and the design principle that fixes it.
08 Articles08_articles/engineering/sim-to-real-cheap-tof-sensors.researchbest
Sim-to-Real for Cheap ToF Sensors
Why a sim-trained drone policy stumbles on noisy ToF sensors, and how domain randomization closes the sim-to-real gap.
08 Articles08_articles/benchmarks/rl_vs_lawnmower
Benchmark — RL vs lawnmower indoor coverage
Quantitative head-to-head: PPO policy vs A* + Frontier exploration on warehouse_v2. Coverage, time, energy, where each wins.
08 Articles08_articles/business_cases/delivery
Business case — last-mile delivery
Autonomous indoor drones for the last 100 meters of logistics: warehouse handoff, return-to-base, GPS-denied final delivery.
08 Articles08_articles/business_cases/monitoring
Business case — industrial monitoring & inspection
Autonomous drones for HVAC, structural inspection, security patrols, and asset monitoring in GPS-denied industrial spaces.
08 Articles08_articles/business_cases/search_rescue
Business case — indoor search-and-rescue
Autonomous drones for indoor SAR: collapsed structures, post-disaster reconnaissance, GPS-denied environments where minutes matter.
08 Articles08_articles/roadmap/2026_h2
Roadmap — H2 2026
What we plan to ship between July and December 2026. Three workstreams: sim-to-real, robustness, real-drone bring-up.
01 Dev-Log01_dev_log/2026/05_may/week_1_simulation_setup
May 2026, Week 1 — Simulation setup
Installing ArduPilot SITL, Gazebo Harmonic, and ROS 2 Jazzy. First MAVLink heartbeats and bringing up the indoor world.
01 Dev-Log01_dev_log/2026/05_may/week_2_first_rl_training
May 2026, Week 2 — First RL runs
The first PPO training run, frontier-reward variant, and an RND-based exploration experiment — the RL framework starts producing.
01 Dev-Log01_dev_log/2026/05_may/week_3_gazebo_physics_tuning
May 2026, Week 3 — Gazebo physics tuning
Tuning motor dynamics and Gazebo plugins so the simulated drone behaves close to the real one we'll eventually build.
01 Dev-Log01_dev_log/agent_reports/firmware_agent_logs
Raw agent reports — firmware
Append-only buffer of firmware-agent (ESP32-S3 embedded developer) entries — pike reports feeding the weekly digests.
01 Dev-Log01_dev_log/agent_reports/researchbest_agent_logs
Raw agent reports — researchbest
Append-only buffer of researchbest-agent web research (20+ topics — SLAM, frontier exploration, Nav2, sensors).
01 Dev-Log01_dev_log/agent_reports/rl_agent_logs
RL Agent Work Logs — Overview
Overview of the reinforcement-learning work on autonomous 2D indoor mapping, with a chronology of dev-log stages and outcomes.
01 Dev-Log01_dev_log/agent_reports/sim_agent_logs
Raw agent reports — simulation
Append-only buffer of simulation-agent entries (ROS 2 + Gazebo + ArduPilot SITL) — pike reports feeding the weekly digests.