Hitesh Kumar
Papers
2
Total Citations
28
H-Index
2
About
Hitesh Kumar is a researcher in robotics and artificial intelligence, with a primary focus on intelligent object manipulation and robotic grasping. His work bridges evolutionary computing and deep reinforcement learning to address one of robotics' most fundamental challenges: enabling machines to grasp and manipulate objects with human-like dexterity. His most-cited paper, "Robotic grasp manipulation using evolutionary computing and deep reinforcement learning" (2021), has accumulated 26 citations, highlighting its impact on the field. In this work, Kumar explores how robots can learn grasping skills through iterative optimization and neural network-based decision-making, drawing inspiration from human motor learning—where even a child's grasp improves over years of practice. By combining evolutionary algorithms with reinforcement learning, he proposes frameworks that allow robots to adapt to novel objects and environments. Kumar's contributions are particularly relevant for advancing autonomous systems in manufacturing, healthcare, and service robotics. His research underscores the potential of hybrid AI approaches to solve complex manipulation tasks, making him a notable voice in the growing intersection of evolutionary computation and robotic control.
Research Focus
Key Achievements
Top Papers
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