Max Robotics — Global Service Robot Directory + US Certification

About

Inara Tusseyeva’s research bridges the critical gap between robotic navigation and human-robot interaction, with a focus on safety and perceived intelligence. Her early work on autonomous underwater vehicles (AUVs) introduced the **3D Global Dynamic Window Approach**, a real-time navigation algorithm that enables self-propelled marine robots to execute complex missions and return to base autonomously—a foundational contribution cited 12 times. Building on this, she shifted to collaborative robotics, investigating how motion planning algorithms affect **perceived safety** in human-cobot interactions. Her 2022 study, with 10 citations, compared fixed-path and real-time algorithms using speed-and-separation monitoring, revealing that algorithm transparency significantly influences human trust. Tusseyeva’s 2024 review on **perceived intelligence** in human-robot interaction (8 citations) synthesizes how users’ perceptions evolve before and after experiments, highlighting the role of habituation. Her survey on physical human-robot safety (6 citations) further consolidates best practices. By combining rigorous algorithmic development with human-factors research, Tusseyeva has shaped safer, more intuitive robotic systems—from deep-sea AUVs to factory-floor cobots—earning her recognition as a leader in human-centered robotics.