Eric Sean Kesuma
Papers
1
Total Citations
11
H-Index
1
About
Eric Sean Kesuma is a researcher at the forefront of industrial automation and intelligent robotics, with a primary focus on integrating artificial intelligence and computer vision into warehouse logistics. His most cited work, "Pallet Detection and Distance Estimation with YOLO and Fiducial Marker Algorithm in Industrial Forklift Robot" (2023, 11 citations), addresses a critical bottleneck in e-commerce efficiency: enabling autonomous forklifts to accurately detect, track, and estimate the distance of pallets in dynamic warehouse environments. By combining YOLO-based object detection with fiducial marker algorithms, Kesuma’s research provides a robust, real-time solution for automated picking systems, directly enhancing the operational reliability of industrial robots. This contribution is pivotal for scaling smart warehousing and reducing human error in material handling. His work exemplifies the practical deployment of deep learning in robotics, bridging the gap between theoretical AI models and tangible industrial applications. With growing citation impact, Kesuma is establishing himself as a key voice in the evolution of autonomous logistics, where precision and speed are paramount.
Research Focus
Key Achievements
Top Papers
- 1