Tammana Akhil
Papers
2
Total Citations
14
H-Index
2
About
Tammana Akhil is a robotics researcher focused on integrating perception and control for assistive applications. Their work centers on bridging vision and speech processing to enable more intuitive human-robot interaction, particularly through the Robot Operating System (ROS). Akhil’s most cited paper, “Integration of Vision based Robot Manipulation using ROS for Assistive Applications” (2020, 11 citations), demonstrates how real-time object recognition with YOLOv3 can empower robots to autonomously manipulate objects for assistance tasks. Building on this, their 2021 study on “Integration of Speech and Vision for Perception in Assistive Robots” (3 citations) advances multimodal perception, combining auditory and visual cues to improve robot responsiveness in dynamic environments. By leveraging ROS as a flexible middleware, Akhil’s contributions offer scalable frameworks for developing affordable, intelligent assistive robots that can aid the elderly or disabled. Their work highlights the practical potential of deep learning and sensor fusion in real-world robotics, making a tangible impact on accessible automation.
Research Focus
Key Achievements
Top Papers
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