Real-time Perception and Autonomous Navigation: A Fuzzy Logic-Based Approach for Enhanced Obstacle Avoidance in Self-Driving Vehicles

Our proposed work discusses the design of fuzzy logic controllers for navigating self-driving vehicles in environments with stationary and moving obstacles. The controllers are rule-based and adaptive to varying obstacle sizes, and incorporate data from sensors and CNNs. Simulation results show promise for future use. However, further work will include designing controllers for varying speeds of moving obstacles and increasing the number of sensors for multi- vehicle environments to enhance the performance of the vehicle.

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