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About

Abhishek Ranjan is pioneering the intersection of deep learning and agricultural robotics to address critical labor shortages and quality losses in fruit harvesting. His core research focuses on developing intelligent perception and manipulation systems for specialty crops, with a particular emphasis on mangoes and cotton. Ranjan’s most impactful work, “Detection and Localisation of Farm Mangoes using YOLOv5 Deep Learning Technique” (12 citations), tackles the formidable challenge of fruit detection under real-world conditions—overcoming occlusion, shadows, and variable lighting to enable precise, automated identification. He extends this perception capability into robotic control with his work on “Optimizing cotton-picking robotic manipulator and inverse kinematics modeling using evolutionary algorithm-assisted artificial neural network” (10 citations), where he employs particle swarm optimization to solve complex inverse kinematics for a 4-DoF cotton harvesting robot. Most recently, his 2024 study on a “peduncle-holding end effector for robotic harvesting of mango” addresses the delicate task of grasping fruit without causing bruising or sap-induced infections—a critical bottleneck in post-harvest quality. Through these contributions, Ranjan is building a complete pipeline from vision to manipulation, advancing the feasibility of autonomous harvesting for high-value crops.