COLLISION AVOIDANCE IN DRONE SWARMS

This research examines fundamental approaches and algorithms driving the rapid growth of the market for collision avoidance systems, analyzing three critical architectural paradigms: (1) centralized versus decentralized control systems, (2) geometric approaches versus machine learning implementations, and (3) potential field methods in dense multi-agent environments. Centralized architectures offer superior coordination and global optimization but suffer from scalability limitations and single points of failure, while decentralized systems provide enhanced robustness and scalability at the cost of optimal global coordination

COL001 - Fundamental Approaches and Algorithms
COL002 - Sensing and Perception Technologies
COL003- Communication and Coordination
COL004 - Real-Time Performance and Constraints
COL005 - Scalability and Emergent Behavior
COL006 - Safety and Reliability
COL007 - Environmental and Operational Challenges
COL008 - Integration and Standards