Vishnu Kant
Papers
2
Total Citations
3
H-Index
1
About
Vishnu Kant is at the forefront of advancing autonomous navigation, specializing in bio-inspired computational intelligence for mobile robotics. His research centers on developing novel metaheuristic algorithms that enable real-time, adaptive path planning in complex and dynamic environments. Kant’s major contributions include pioneering the Black-Winged Kite Algorithm (BWKA), a nature-inspired optimizer that mimics the flight patterns of black-winged kites to balance exploration and exploitation, achieving efficient path optimization for four-wheeled mobile robots. He further innovated with the Hybrid Slime Mold Algorithm, integrating the Slime Mold Algorithm (SMA) with the Triangle Inequality Principle and Partition Method Strategy to enhance collision avoidance and real-time responsiveness in environments with moving obstacles. Though his most-cited works are recent (2025), they have already garnered attention, with the BWKA paper accumulating 2 citations and the hybrid SMA study 1 citation, signaling growing impact in the field. Kant’s work is notable for its practical orientation, directly addressing the critical challenge of dynamic obstacle avoidance—a key bottleneck in autonomous vehicle deployment. His algorithms offer a fresh, efficient alternative to traditional path planners, positioning him as an emerging leader in adaptive robotics and swarm intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2