Goutam Mishra

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About

Goutam Mishra is a robotics researcher whose work focuses on intelligent navigation and control systems for autonomous mobile robots. His primary research areas include neural network-based robot control, path planning algorithms, and intelligent system design for real-world robotic applications. Mishra’s most impactful contribution is his 2014 paper, "Neural network approach to control wall-following robot navigation," which has garnered 16 citations. In this work, he developed a neural network-based controller that enables robots to navigate efficiently from a source to a destination—a fundamental challenge in robotics. His earlier 2013 paper, "A Novel Approach for Intelligent Robot Path Planning" (6 citations), proposed an innovative algorithm for determining optimal paths between start and end positions using antenna-equipped intelligent systems. Together, these works address critical bottlenecks in autonomous navigation: control precision and path optimization. Mishra’s research is particularly valuable for students and engineers working on mobile robotics, offering practical, bio-inspired solutions for wall-following and obstacle avoidance. His contributions demonstrate the power of neural networks in creating adaptive, real-time navigation systems, laying groundwork for more sophisticated autonomous robots in industrial and service applications.