Sarcouncil Journal of Applied Sciences Aims & Scope

Abstract: Event cameras represent a transformative advancement in visual sensing technology, drawing inspiration from biological retinas to capture brightness changes asynchronously at the pixel level. Unlike conventional frame-based cameras that suffer from motion blur and limited dynamic range, event sensors achieve microsecond temporal resolution and exceptional performance, exceeding 120 dB dynamic range. This novel hybrid perception system synergistically combines event-based vision with LiDAR sensing to overcome individual sensor constraints while leveraging their complementary strengths. The fusion architecture addresses fundamental challenges in autonomous perception through sophisticated temporal synchronization, noise filtering, and heterogeneous data representation strategies. Applications span diverse domains from high-speed drone navigation and advanced driver assistance systems to robotic manipulation and space missions. The hybrid system demonstrates superior performance in challenging scenarios, including extreme lighting variations, rapid motion, and feature-poor environments where traditional sensors fail. Through continuous-time estimation frameworks and neural fusion models, the system maintains robust operation across the full spectrum of real-world conditions. This technological convergence opens new possibilities for autonomous systems to operate in previously inaccessible domains, establishing a foundation for next-generation perception capabilities that match biological vision's adaptability while maintaining the precision required for autonomous operation.