Testing of Swarm

Mission:
Scanning of runway in coordinated manner

Goal  Achieved

• Synchronized takeoff
•  Coordination is achieved decentrally through fundamental swarming rules:
• Effective collision avoidance
• Transferring swarm simulation parameter to real 

• Mission:
  This drone is designed to clean vertical surfaces using pressurized fluid, all while maintaining precise distance and stability near walls or structures. The similar concepts are applicable for fire fighting drone.    

Goal Achieved:  

• 🧭 Dynamic Payload Management
  Designed a control system capable of maintaining stability despite real-time shifts in center of gravity and inertia caused by fluctuating water levels.
• 💦 Reaction Force Compensation
  Engineered the drone to remain stable under varying water jet pressures, accounting for reactive forces and optimizing the thrust-to-weight ratio accordingly.
• 📏 Real-Time Precision Navigation
  Achieved accurate wall-following through the integration of real-time sensor feedback and control algorithms, maintaining optimal cleaning distance with collision avoidance

Concept: Delivering a payload precisely over the target: Fireball over fire, grenade over target. 

Goal Achieved

• 🧠 Onboard Target Detection
  
• 🎯 High-Speed Accuracy
  
• 🌀 Optimized Final Approach
  
• 🛠️ Post-Drop Stability Control
  

🛫 Behind the Scenes: First Flight Readiness

• Risk Assessment Protocols – What pre-flight checks are essential before initial lift-off?
   
• Ensuring Safety – How do we ensure takeoff won’t cause instability or twisting?
   
• Flight Mode Selection – Which flight mode offers maximum control and safety for the first attempt?
   
• In-Flight Diagnostics – What indicators do we monitor post-liftoff to validate system stability?
   
• Emergency Preparedness – What fail-safes and contingency plans are in place?
   
• Controller Tuning Strategy – When is it safe to proceed with tuning parameters?