Kritika Anand
Papers
1
Total Citations
8
H-Index
1
About
Kritika Anand is a researcher advancing the field of embodied AI and robotic navigation, with a primary focus on object-goal navigation (ObjectNav). Her most cited work, "Spatial Relation Graph and Graph Convolutional Network for Object Goal Navigation" (2022, 8 citations), introduces a novel framework that enables robots to locate and navigate to specific object instances from arbitrary starting positions. By leveraging a history of robot trajectories, Anand developed a Spatial Relational Graph (SRG) that captures spatial dependencies between objects, combined with a Graph Convolutional Network to enhance decision-making. This contribution addresses a critical challenge in autonomous robotics: efficiently searching for target objects in unknown environments. Her work stands out for integrating graph-based reasoning with deep learning, offering a more structured approach to navigation than traditional methods. Though early in her career, Anand’s research has already garnered attention for its practical implications in service robotics and home automation. Her innovative use of spatial relations promises to make robots more intuitive and capable in real-world settings, marking her as a rising talent in the intersection of computer vision, robotics, and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1