Description:
Micro-drones or “bugs”(as I like to call them) present immense opportunities for carrying out critical search, surveillance and defense operations in tight spaces where larger drones cannot access.
Small bug drones equipped with sensors, imaging capabilities, navigation systems and potentially small payloads offer mobility, maneuverability and access to areas that larger systems may not. This agility could aid disaster response teams, infrastructure inspectors, military and security personnel to better assess situations, threats, damages and plan responses while reducing risks to human operators.
However, significant technological barriers remain in navigation, coordination and functionality of bug-sized drones before this potential can be realized. Drooid seeks to research and develop an innovative Swarm Gradient Bug Algorithm (SGBA) that would enable autonomous swarms of bug drones to efficiently explore unfamiliar environments and return home safely. The SGBA approach would direct outward-bound bugs to optimize coverage area while leveraging inter-drone communication to maximize search efficiency and avoid collisions. Inward journeys would be facilitated by gradient search techniques leading swarms back to their departure beacon. Underpinning technologies involve integrating blockchain for data security and artificial intelligence for continual improvements in navigation, coordination and object recognition capabilities
At the core, our Swarm Gradient Bug Algorithm (SGBA) allows groups of micro-drones with limited flight ranges to explore unfamiliar areas for data gathering while ensuring the capability to return home. We achieve this through distributed coordination between drones leveraging point-to-point visual analysis, optimized waypoint traversal techniques borrowed from insect swarming behaviors, and blockchain to enable position triangulation with proven identity tokens for each drone during transit.
Practically, this equates to launching interconnected drone swarms that act as resilient mobile data harvesting nodes. For example, in a search and rescue context, police could deploy our drone system at a quake site to fully map rubble just by specifying the general diameter of needed coverage. Our algorithm handles directing sub-teams of 2-5 drones to thoroughly canvass the area using lidar, infrared sensors, or high-res cameras per the client’s data capture payloads. The cryptographic tracking then allows precise monitoring during their fanning patterns as well as reliable return sequence back to base for operator synthesis and recharging.
We’ve been running a simulated scaled test mapping in mock disaster zones up to 60 acres and successfully commanded returns of 85% drones within 8% energy reserves of depletion.
Vision:
We are building the future of autonomous systems for critical missions by democratizing drone swarm capabilities to expand access and applications for environmental monitoring, deterrence, and first response while upholding security and privacy standards.We are committed to pioneering advanced intelligence solutions for submarines, land, aerial, and maritime operations.
Problem:
Search and rescue teams struggle to rapidly locate survivors trapped in rubble after disasters. Infrastructure inspectors risk their lives entering toxic confined spaces. Military operations to deter and selectively neutralize imminent terrorist threats put civilians and personnel in harm’s way. All these critical missions share a desperate need for capability where it otherwise cannot go - the ability to safely enter dangerous spaces inaccessible to human operators, quickly gather critical environmental data, and coordinate an informed, strategic response.
While promises exist of drone technologies addressing these capability gaps, existing drones are too large, loud, resource-intensive and limited in functionality. Micro-drones show potential but get easily lost, crash frequently, and lack the speed, endurance and intelligent coordination to reliably perform critical missions. What is desperately needed is breakthrough technology allowing swarms of micro-bug drones to autonomously navigate, coordinate, and function effectively as a mobile sensory extension of human operators working under extreme time pressure.
We cannot afford to send rescue teams in blind, put inspectors personally in harm’s way, or accept avoidable casualties and collateral damage during defense operations. Enhancing mission capability while ensuring operator safety demands investing now in realizing the immense potential of drone swarms through a transformative navigation and coordination algorithm we call SGBA. We owe it to trapped disaster victims, infrastructure safety, and civilian protections to develop and field this solution with utmost urgency. The alternative of inaction promises only repeated, preventable tragedy.
Solution
Drooid’s Swarm Gradient Bug Algorithm seeks to achieve a breakthrough in microdrone coordination, navigation and autonomy by synergistically combining the distributed adaptability of bioinspired swarm systems with the global connectivity of blockchain.
Swarm systems are robust, scalable and adaptable to complex environments due to simple local interactions, not unlike natural systems from bacterial colonies to flocks of birds. However, recent research shows complementing local coordination with some global knowledge exchange can aid navigation in unknown terrain and synchronize subgroups within a swarm. Drooid’s innovation is unifying these localized and global information streams to enable resilient, efficient coordination between bug drones.
Each bug drone possesses processors for distributed flight control, navigation, video processing and object detection. Neighboring drones continuously exchange telemetry data to collectively map surroundings and adapt movements to terrain, obstacles and each other. This localized communication enables robust exploration without relying on fragile GPS signals. Yet bugs also tap into global data on the swarm and mission environment streamed from an encrypted blockchain ledger. This provides critical contextual awareness for navigating back to their origin point[6].
Validation
- Projected Market Growth: The global surveillance market is expected to reach $160 billion by 2030 growing at a CAGR of 12.91% from 2023 to 2030., indicating significant growth opportunities for innovative security solutions (source: Market Research Report).
- Emerging Markets and Infrastructure Projects: Developing countries are witnessing rapid infrastructure development, fueled by economic growth and urbanization. These emerging markets present opportunities for deploying advanced asset inspection & and security patrol solutions as new infrastructure projects are planned and implemented.
Team Background and experience
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- 2x Founder & Entrepreneur. Designer and software engineer, specializing in machine learning, computer vision, and neural networks. Resume
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Chiranjeewee Prasad Koirala, Github
- AI researcher with a strong background in machine learning, natural language processing, and deep neural networks.
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Kunsang Tsering, Linkedin, Github
- software engineer with a knack for designing and implementing robust and scalable solutions. Experienced in the full software development lifecycle, from concept to deployment.
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Vibhuti Dabas LinkedIn , Github
- Blockchain Architect Proficient in various programming languages and frameworks, with a focus on creating efficient and user-friendly applications
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Yao (Bella) Chen, LinkedIn
- Software Engineer, Experienced in AI and infrastructure at all stages of product life-cycle.
Grant Request $
We need a $20k grant to reach our next project milestone.
budget breakdown
01
Quadcopter Frames: $70 per frame = $700
02
Flight Controller: $50 per controller= $500
03
Motors and Propellers (Set of 4): $30 per set =$300
04
Battery Packs: $30 per pack =$300
05
Electronic Speed Controllers (ESC): $20 per ESC = $200
06
Onboard Microcontroller (e.g., Raspberry Pi or Arduino): $60 per unit= $600
07
Sensors (e.g., GPS, Gyroscope, Accelerometer): $30 per sensor= $300
08
Communication Modules (e.g., Wi-Fi or Bluetooth): $30 per module =$300
09
Chassis and Body Materials: $20 per drone =$200
10
Miscellaneous Components (wires, connectors, etc.): $30 per drone= $300
11
Lab Access Rent (4 months) per month $2,500= $10,000
12
Team Snacks= $1000
13
Transportation= $2000
14
Miscellaneous= $4000
TOTAL BUDGET
$20,700
Milestone to accomplish
Our proposed project for the next 4-5 months involves allocating $20k for tooling and software to build out our prototype, with the remainder earmarked for lab access rent. We have received over 400 applications from talented engineers willing to join and work on the project for free.
-simulation of prototype with bug algorithms
-integrate decentralized decision making algorithms
-Build out a 10 swarm bug drones based on the simulation
-conduct initial test in a simulated environment
-Refine and optimize swarm intelligence algorithms
Additional Resources
I would appreciate it if you could review our full project proposal. In it, we provide a detailed overview of the problem we aim to solve, the technical details and challenges involved, our proposed solutions, and reasons why we are qualified to address this issue.
Link to the full proposal: https://shorturl.at/ikptx
Project Deck: https://shorturl.at/eklUY
website: https://drooid.xyz/
twitter:https://twitter.com/drooidHq
Discord: https://discord.com/invite/AAXCmJk6Mt
Project Bounties: Bounties - Google Sheets