Geeta Chhabra Gandhi

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About

Geeta Chhabra Gandhi is a robotics researcher whose work sits at the intersection of autonomous navigation, computer vision, and resource-constrained computing. Her primary research areas include simultaneous localization and mapping (SLAM), monocular depth estimation, and visual odometry—core technologies that enable robots to understand and move through unknown environments. Gandhi’s most notable contribution is her 2025 paper on hybrid robot navigation, which integrates monocular depth estimation with visual odometry to achieve efficient navigation on low-resource hardware. This work, already garnering 6 citations, addresses a critical bottleneck in deploying autonomous systems on embedded platforms with limited computational power. She has also contributed a chapter on machine learning applications in SLAM algorithms, demonstrating her ability to synthesize complex technical concepts for broader audiences. Gandhi’s research is particularly significant for advancing practical, cost-effective robotic solutions that can operate without expensive sensors or high-end processors. Her focus on algorithmic efficiency and hardware-aware design positions her work at the forefront of making autonomous navigation accessible for real-world applications, from service robots to exploratory drones.