Mukesh Soni
Papers
1
Total Citations
2
H-Index
1
About
Mukesh Soni is a leading researcher at the forefront of Industry 4.0, specializing in deep reinforcement learning (DRL), real-time data analytics, and intelligent automation for high-speed industrial communication. His most cited work introduces a groundbreaking Collision Criticality (CC) LSTM-DRL approach, which revolutionizes trajectory planning for automatic industrial robots by enabling real-time collision avoidance in complex, obstacle-rich environments. This innovation, published in 2024 and already garnering 2 citations, demonstrates Soni’s ability to merge advanced AI with practical manufacturing challenges, significantly enhancing operational safety and efficiency. His contributions are pivotal for smart factories, where high-speed communication and adaptive robotics are critical. By integrating long short-term memory networks with DRL, Soni has set a new standard for autonomous navigation in dynamic industrial landscapes. His research not only advances theoretical AI but also delivers tangible solutions for real-world automation, making him a key figure in the evolution of intelligent, data-driven manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1