Max Robotics — Global Service Robot Directory + US Certification

About

Sudarshan Sanap is a robotics researcher focused on autonomous navigation in uncertain environments, with a particular emphasis on drone and mobile robot path planning. His work addresses the critical challenge of enabling unmanned aerial vehicles (UAVs) and ground robots to operate safely and efficiently when faced with unpredictable obstacles and dynamic conditions. Sanap’s key contributions include a topological approach to drone navigation that leverages environmental structure for robust pathfinding, a hybrid Firefly Algorithm-Genetic Algorithm (FA-GA) controller that combines swarm intelligence with evolutionary optimization for mobile robot motion, and a probability-based fuzzy logic system for UAV obstacle avoidance in static uncertain settings. He has also developed a Matrix-based Genetic Algorithm (MGA) that improves convergence speed and computational efficiency for 3D UAV path planning. With over 20 citations across his most-cited works, Sanap’s research is gaining traction among scholars working on intelligent autonomous systems. His innovative hybrid and matrix-based methods offer practical solutions for real-world deployment in surveillance, smart transportation, and search-and-rescue operations, making him a promising voice in the field of autonomous navigation.