Research and Projects
Featuring projects that combine traditional methods with vision-language models (VLMs). From object detection to real-time video analysis, each project is built to solve real-world problems through intelligent visual systems.
Featuring projects developed for humanoids, autonomous mobile robots (AMRs), and industrial robotic systems. From perception to navigation, I use ROS-based frameworks to design intelligent, responsive machines for real-world applications.
Focusing on perception, balance, situational awareness, and safe human-robot interaction. These projects explore how embodied intelligence can bring robots closer to real-world adaptability and trust.
From dynamic obstacle avoidance to global and local navigation strategies for AMRs, humanoids, and industrial robots. These projects focus on creating safe, efficient, and adaptive motion in real-world environments.
From deep learning and reinforcement learning to transformer models and vision-language systems. These works focus on enabling robots to learn, adapt, and make intelligent decisions in complex environments.
Spanning large language models (LLMs), small language models (SLMs), vision-language models (VLMs), and autonomous AI agents. Each system is designed to reason, perceive, and interact intelligently with the world.
From dynamic obstacle avoidance to global and local navigation strategies for AMRs, humanoids, and industrial robots. These projects focus on creating safe, efficient, and adaptive motion in real-world environments.
