Arindam Bhakta
Papers
1
Total Citations
2
H-Index
1
About
Arindam Bhakta's research lies at the intersection of robotic active vision, probabilistic modeling, and bio-inspired control systems. His most notable contribution is the development of utility function generated saccade strategies, a probabilistic framework that enables robots to intelligently direct their gaze by mimicking the rapid, goal-driven eye movements of biological systems. This work, published in 2018, introduces a novel approach to active vision where saccade decisions are optimized based on expected information gain, allowing robots to efficiently sample their environment for tasks such as object recognition and navigation. While his citation count remains modest—with his key paper garnering 2 citations—Bhakta's work is foundational in bridging computational neuroscience and robotics, offering a principled method for autonomous visual exploration. His research has implications for improving robot perception in dynamic, unstructured settings, and his probabilistic approach provides a rigorous mathematical foundation for future advances in active vision systems. Bhakta's contributions are particularly relevant for students and researchers interested in the intersection of decision theory, sensorimotor control, and embodied intelligence.
Research Focus
Key Achievements
Top Papers
- 1