Max Robotics — Global Service Robot Directory + US Certification

About

Minh Do Hoang is a roboticist whose work centers on the critical challenge of enabling mobile robots to safely and reliably interact with humans in dynamic, mixed environments. His primary research areas include human-robot interaction, autonomous navigation, and perception systems. Hoang’s most impactful contribution is his human-following strategy for mobile robots, which has garnered 19 citations and addresses the complex task of robots tracking and accompanying people in cluttered spaces. He further advanced this field by proposing a reliable recovery mechanism for person-following robots when the target is lost, using a probabilistic Kalman Filter approach to predict unexpected human positions based on prior data—a paper cited 11 times. Demonstrating his versatility, Hoang also developed MoDeT, a low-cost obstacle tracker for self-driving mobile robots using 2D laser scans, which enhances collision avoidance and safety. Earlier in his career, he contributed to perception sensor networks, fusing data from multiple Kinects and PTZ cameras for seamless human identification and tracking. With a portfolio of papers that collectively inform safer, more autonomous robot navigation, Hoang’s work is foundational for students and researchers developing robots that can work alongside humans in real-world settings.