Inmaculada Coma

Universitat de València, Parc Científic de la Universitat de València

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About

Inmaculada Coma’s research bridges the physical and virtual worlds, with a primary focus on **motion cueing algorithms** for vehicle simulators and **robotic-assisted surgery (RAS)** planning. Her most influential work, “Towards a simulation-based tuning of motion cueing algorithms” (38 citations), tackles the critical challenge of optimizing how robotic motion platforms generate realistic inertial cues—a problem she later advanced by applying **particle swarm optimization** to automate the tuning process. This work directly impacts the fidelity of driving and flight simulators used in training and research. Coma also contributes to **biomedical robotics**, co-developing a mixed-platform collaborative virtual RAS planner to address the steep learning curve of surgical robots, enabling systematic setup planning for minimally invasive procedures. Earlier in her career, she explored **computer vision** for autonomous navigation, proposing a high-speed log-polar method for time-to-impact calculation in mobile vehicles—a technique relevant to crash detection and robotic navigation. Her interdisciplinary work, spanning optimization, simulation, and surgical robotics, demonstrates a consistent drive to enhance human-machine interaction through intelligent algorithm design.