Vijayalakshmi A Bakale

Papers

Total Citations

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About

Vijayalakshmi A Bakale is a researcher whose work sits at the intersection of artificial intelligence and spatial computing, with a primary focus on indoor navigation systems. Her most cited paper, "Indoor Navigation with Deep Reinforcement Learning" (2020, 11 citations), addresses a critical challenge: enabling reliable navigation within buildings where GPS signals fail. This work has direct applications in robotics, drone operations, and augmented reality gaming. Bakale's key contribution lies in applying deep reinforcement learning algorithms to develop autonomous navigation solutions that can adapt to complex indoor environments without pre-mapped routes. Her research bridges the gap between theoretical AI models and practical, real-world deployment—a significant achievement given the growing demand for autonomous systems in logistics, healthcare, and smart buildings. While her citation count reflects an emerging career, the novelty of her approach positions her as a promising voice in the field of embodied AI and spatial intelligence. For students and researchers, Bakale's work offers a compelling case study in how reinforcement learning can solve fundamental problems in robotics and human-computer interaction.