Rishi Arran A L Suppramaniam

Papers

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About

Rishi Arran A L Suppramaniam is a robotics researcher whose work focuses on automation, computer vision, and human–robot interaction, with a particular emphasis on developing intelligent systems for dynamic environments. His most cited paper, "Visual Servo Algorithm of Robot Arm Simulation for Dynamic Tracking and Grasping Application" (2022, 3 citations), addresses a critical need accelerated by the COVID-19 pandemic: enabling robots to operate autonomously without human intervention. This work introduces a visual servo algorithm that allows a robotic arm to track and grasp moving objects in real time, contributing to the advancement of contactless automation in industrial and healthcare settings. Though early in his career, Suppramaniam’s research bridges simulation and practical application, offering scalable solutions for dynamic object manipulation. His contributions are particularly relevant as industries seek resilient automation technologies capable of continuous operation during health crises. With a focus on real-time visual feedback and control, his work lays groundwork for more adaptive robotic systems, positioning him as an emerging voice in the field of robotic vision and autonomous grasping.