SMART ROBOT FOR OBSTACLE DETECTION AND AVOIDANCE

We presented a smart robot system for obstacle detection and avoidance using advanced sensing and adaptive navigation techniques. The system achieves high detection accuracy (up to 95%), fast response time (1–2 s), and better navigation efficiency compared to traditional methods. The use of multiple sensors and real-time processing enables smooth and reliable navigation in both static and dynamic environments. The architecture is scalable, efficient, and can adapt to changing conditions through continuous feedback. Future work will focus on improving AI integration, enhancing real-time processing, and enabling multi-robot coordination.   Furthermore, the system shows strong potential for real-world applications such as autonomous vehicles, warehouse automation, and service robots. Its ability to operate efficiently in dynamic environments while maintaining safety and stability highlights its practical value. By combining sensor fusion, path planning, and adaptive control, the system provides a reliable solution for modern robotic navigation challenges. Future improvements may include reinforcement learning, advanced sensor fusion, and large-scale deployment for better performance and scalability

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