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About

R. Sitharthan is a leading researcher at the intersection of assistive robotics, autonomous navigation, and artificial intelligence. His work focuses on developing intelligent systems that bridge the gap between human intention and machine action, with profound implications for healthcare, logistics, and AI-driven perception. Sitharthan’s most impactful contribution is the "Intelligent Robotic Chair With Thought Control and Communication Aid," which uses higher-order spectra band features from EEG signals to enable navigation and communication for differently-abled individuals—a pioneering work that has garnered 68 citations. He has further advanced autonomous robotics through self-adaptive learning particle swarm optimization for path planning in complex 2D Lidar environments, addressing critical gaps in SLAM algorithm evaluation for smart logistics. His recent investigations into bit-size reduced half-precision floating-point formats for image pixel characterization are pushing the boundaries of efficient AI deployment in robotics and deep learning. With a research portfolio that seamlessly integrates thought-controlled interfaces, optimized navigation, and computational efficiency, Sitharthan is shaping the future of human-centered robotics and intelligent automation.