Drone Swarm Coordination via Centroid Control and Collision Avoidance
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Solution Overview
Problem
Existing drone systems face challenges in coordinating multiple drones to fly in proximity without collisions and maintaining a cohesive mission path, especially in dynamic environments like surveillance operations, where human supervision is not always feasible.
Innovation Solution
The system employs a swarm coordination method inspired by flocking behaviors, using virtual regions around each drone to ensure collision avoidance and maintain a group centroid within a specified sphere, allowing drones to adjust their flight paths dynamically while following a predetermined path, with a handheld device coordinating the swarm and onboard processors managing communication and obstacle avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If drones are coordinated to fly in proximity to form a swarm, then surveillance capabilities and operational efficiency are improved, but collision risk and coordination complexity increase
Solution Approach 1:
Each drone is equipped with onboard processors that autonomously compute its position relative to the group centroid and determine necessary flight adjustments without external intervention. The system implements self-service by having individual drones independently calculate their contributions to group movements and autonomously navigate to maintain swarm cohesion while avoiding collisions.
2Reliability
If drones maintain fixed formation, then collision avoidance is improved, but adaptability to dynamic environments deteriorates
Solution Approach 1:
The swarm formation is designed as a dynamic system where each drone continuously adjusts its position based on real-time calculations of group centroid movements. Rather than maintaining rigid fixed positions, drones adapt their relative placements dynamically while preserving safety margins, enabling the formation to respond to environmental changes and obstacles while preventing collisions.
3Measurement precision
If human supervision is provided for drone operations, then mission control accuracy is improved, but operational autonomy and response time deteriorate
Solution Approach 1:
The system implements continuous feedback loops where onboard processors monitor the positions of all group members, calculate the group centroid's movement, determine each drone's contribution to the movement, and adjust flight paths accordingly. This automated feedback mechanism maintains high mission control accuracy by continuously optimizing swarm behavior without requiring human intervention, thereby achieving both precision and autonomy.
Data Source
AI summary
A method, system and apparatus to detect when one or more airborne unmanned aerial vehicles (drones) are close to each other, and to take necessary actions to maintain a minimum distance between drones as well as a maximum distance among the drones in a dynamic environment by automatic navigation. A computer method and apparatus for holding a group of drones in a swarm formation by maintaining the group centroid of the group of drones within a tolerance of a predetermined location is also disclosed. Additionally, methods to move a swarm of drones along a predetermined path while maintaining the swarm formation of the drones is also disclosed.