Sandeep Konam

Rajiv Gandhi University of Knowledge Technologies

Papers

Total Citations

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About

Sandeep Konam is a robotics and artificial intelligence researcher whose work bridges the gap between deep learning-based perception and real-world autonomous systems. His most recognized contribution, "Obstacle Avoidance through Deep Networks based Intermediate Perception" (2017, 34 citations), addresses one of robotics' fundamental challenges — enabling robots to navigate complex environments using monocular images. By leveraging deep learning to overcome the limitations of traditional structure-from-motion techniques, particularly in textureless environments, Konam demonstrated a compelling approach to autonomous navigation that has resonated widely within the robotics community. Beyond autonomous systems, Konam has shown a strong commitment to applying robotics for societal benefit, particularly in agriculture. His early work on the Agricultural Aid for Mango Cutting (AAM) system (2014, 14 citations) and the ROTAAI agricultural robot design (2014, 5 citations) explored how unmanned aerial vehicles, machine vision, and cost-effective robotic platforms could modernize labor-intensive farming practices. These contributions reflect a researcher driven not only by technical innovation but also by practical impact. Collectively, Konam's work highlights a compelling research trajectory — from agricultural automation to intelligent perception — making him a noteworthy voice in applied robotics and computer vision.