Papers
4
Total Citations
54
H-Index
4
About
Dr. Tirtharaj Dash is a researcher whose work lies at the intersection of robotics, neural networks, and bio-inspired optimization. His primary research areas focus on intelligent control systems for autonomous mobile robots, particularly in the domain of wall-following navigation and path planning. Dr. Dash’s most significant contributions involve the development of novel neural network-based controllers that enable robots to navigate complex environments with greater autonomy and precision. Notably, he pioneered the use of a Gravitational Search (GS) algorithm to train feed-forward neural networks for robot control, a method detailed in his most cited work (22 citations). This approach, along with his exploration of Adaptive Resonance Theory (ART-1) for navigation, demonstrates a consistent effort to integrate computational intelligence with real-world robotic applications. His cumulative work, including foundational studies on path planning, has garnered over 50 citations, establishing him as a contributor to the advancement of intelligent, self-navigating systems. Dr. Dash’s research offers practical solutions to the enduring challenge of efficient and reliable robot navigation, making his work a valuable reference for students and researchers in robotics and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2Neural network approach to control wall-following robot navigation16 citations · 2014
- 3
- 4A Novel Approach for Intelligent Robot Path Planning6 citations · 2013