P. V. Srihari

Papers

Total Citations

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About

P. V. Srihari is a researcher at the forefront of intelligent robotics and autonomous navigation, with a primary focus on integrating deep reinforcement learning into real-time robotic systems. His most cited work, "Real Time Path Planning of Robot using Deep Reinforcement Learning" (2020, 10 citations), tackles the critical challenge of enabling robots to navigate dynamic, fully mapped environments while avoiding both static and dynamic obstacles. This contribution is notable for its practical approach to real-time decision-making, allowing an agent to compute collision-free paths from a start to a goal position without pre-computed trajectories. Srihari’s research bridges the gap between theoretical reinforcement learning algorithms and real-world robotic applications, emphasizing adaptability and computational efficiency. His work has been cited by peers exploring autonomous navigation, sensor integration, and intelligent control systems, highlighting its foundational role in advancing robot path planning. By addressing the complexities of dynamic obstacle avoidance in real time, Srihari has provided a valuable framework for future developments in autonomous vehicles, warehouse robotics, and service robots, establishing him as a key contributor to the evolution of intelligent, self-navigating machines.