Papers
72
Total Citations
1,777
H-Index
20
About
Amit Konar is a prominent researcher whose work spans intelligent robotics, brain-computer interfaces (BCI), and computational intelligence, with his contributions leaving a measurable mark on both theory and application. His landmark 2013 paper introducing a deterministic improved Q-learning algorithm for mobile robot path planning has garnered over 270 citations, establishing him as a leading voice in reinforcement learning-based navigation. Konar has also made significant strides in multi-robot coordination, proposing swarm-inspired approaches using artificial bee colony optimization and differential evolution algorithms to solve complex cooperative path-planning challenges. Equally impactful is his pioneering work in EEG-based human-robot interaction. By harnessing motor imagery signals, error-related potentials, and advanced classifiers such as LDA, QDA, and interval type-2 fuzzy logic systems, Konar has helped bridge neuroscience and rehabilitation robotics, enabling individuals with disabilities to control robotic systems through thought alone. His research in this domain has collectively attracted hundreds of citations, underscoring its real-world relevance. Further broadening his portfolio, Konar has addressed uncertainty management in noisy multiobjective optimization environments, demonstrating a rare versatility that makes his body of work indispensable reading for students and researchers at the intersection of AI, robotics, and neural engineering.
Research Focus
Key Achievements
Top Papers
- 1A Deterministic Improved Q-Learning for Path Planning of a Mobile Robot270 citations · 2013
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- 3Multi-robot path-planning using artificial bee colony optimization algorithm101 citations · 2011
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- 5Synergism of Firefly Algorithm and Q-Learning for Robot Arm Path Planning92 citations · 2018
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- 9Cooperative multi-robot path planning using differential evolution70 citations · 2009
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