Papers
40
Total Citations
661
H-Index
13
About
Abhishek Kumar Kashyap is a robotics and intelligent systems researcher whose work sits at the intersection of autonomous navigation, humanoid robot control, and nature-inspired optimization. His research has made significant contributions to solving two of robotics' most persistent challenges: enabling mobile robots to navigate complex, obstacle-laden environments and maintaining dynamic stability in bipedal humanoid systems. Kashyap's investigations into humanoid robot control — particularly involving the NAO platform — have garnered considerable attention, with his Particle Swarm Optimization-aided PID gait controller accumulating 88 citations and his hybrid path-planning technique earning 65. His application of whole-body control with simulated annealing and ant colony optimization-tuned MPC controllers demonstrates a sophisticated command of bio-inspired computational methods for real-world stabilization problems. Equally notable is his work on autonomous mobile robots, where his Multiple ANFIS architecture-based navigation approach has attracted 70 citations, underscoring its practical relevance. With over 430 total citations across his most prominent works and contributions spanning fuzzy logic, whale optimization, and teaching-learning-based algorithms, Kashyap has established himself as a productive voice in intelligent robotics. His 2018 critical review of nature-inspired motion planning techniques further reflects his breadth of knowledge and commitment to synthesizing progress across the field for emerging researchers.
Research Focus
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