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Yogi Dwi Mahandi is a robotics researcher whose work spans multi-object tracking, mobile robot navigation, and legged locomotion. His most cited paper, "An Implementation of Multi-object Tracking Using Omnidirectional Camera for Trash Picking Robot" (8 citations), addresses the critical challenge of automated waste management through computer vision and robotic manipulation. He further advanced autonomous navigation with "Exploration of genetic network programming with two-stage reinforcement learning for mobile robot" (8 citations), introducing a novel learning approach for robots operating in unfamiliar environments. Mahandi has also made significant contributions to educational robotics, developing a six-legged animaloid trainer (7 citations) to inspire students in robotics courses and competitions. His recent work focuses on search-and-rescue (SAR) robots, including inverse kinematics for leg design (2023) and MPU6050-based stabilization using ROS and PID control (2024), both demonstrating practical applications for challenging terrain. With a total of over 30 citations across his publications, Mahandi’s research consistently bridges theoretical advances—such as neighborhood probability mapping for humanoid robot self-localization—with real-world implementations, making him a notable figure in Indonesian robotics and autonomous systems development.