S. C. Mandhata

Papers

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About

S. C. Mandhata is a researcher in mobile robotics and autonomous navigation, with a focus on intelligent path-planning and vision-based control. Their most cited work, "An Improved Q-learning Algorithm for Path-Planning of a Mobile Robot" (2012, 23 citations), addresses a critical limitation of classical Q-learning—its high computational cost and memory requirements for storing Q-values across all state-action pairs. Mandhata proposed an alternative approach that significantly reduces convergence time, enabling more efficient real-time navigation without requiring an optimal starting path. This contribution is particularly valuable for resource-constrained robotic systems. In related work, "Vision based Object Tracking by Mobile Robot" (2012, 8 citations), Mandhata demonstrated practical object tracking using a Khepera II mobile robot equipped with a wireless camera, employing color segmentation via image thresholding to achieve real-time tracking. Together, these works highlight Mandhata’s expertise in combining reinforcement learning with computer vision to enhance autonomous robot behavior. Their research offers accessible, implementable solutions for students and engineers working on mobile robot autonomy, bridging theoretical algorithms with tangible robotic applications.