Medhasvi Kulshreshtha

Manipal University Jaipur, Manipal Academy of Higher Education

Papers

Total Citations

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About

Medhasvi Kulshreshtha is a robotics researcher whose work centers on autonomous systems for environmental sustainability, specifically through the development of trash-collecting robots. Their major contributions lie in integrating advanced computer vision and mechanical design to create fully autonomous outdoor cleaning solutions. In their most-cited paper, "OATCR: Outdoor Autonomous Trash-Collecting Robot Design Using YOLOv4-Tiny" (51 citations), Kulshreshtha pioneered the use of a Rocker-bogie mechanism for resilient terrain navigation and systematically compared Mask-RCNN, YOLOv4, and YOLOv4-tiny for real-time trash detection, achieving a robust, self-operating prototype. Their subsequent reviews on garbage detection and path-planning (8 citations) and trash-collecting robots (5 citations) synthesize critical approaches in image processing and machine learning, providing a foundational roadmap for the field. By tackling the mundane yet vital task of waste collection, Kulshreshtha’s work demonstrates how robotics and deep learning can automate labor-intensive environmental chores, offering scalable solutions for cleaner public spaces. Their research is particularly notable for bridging mechanical innovation with cutting-edge object detection, making autonomous cleaning both practical and efficient.