Max Robotics — Global Service Robot Directory + US Certification

About

Iker Gonzalez is a researcher at the forefront of human-robot interaction and dexterous manipulation, with a focus on tactile sensing, trust, and security in robotic systems. His work bridges the gap between hardware and human perception, exploring how robots can better sense and respond to their environments. In his most-cited paper, "Direction of Slip Detection for Adaptive Grasp Force Control with a Dexterous Robotic Hand" (21 citations), Gonzalez developed a novel tactile communication method using neural networks to classify the direction of object slippage, enabling adaptive grasp control for collaborative human-robot teams. This contribution enhances the reliability of dexterous robotic hands in real-world applications. Gonzalez also investigates the psychological impact of robotic failures, as seen in "Simulated robotic device malfunctions resembling malicious cyberattacks impact human perception of trust, satisfaction, and frustration" (7 citations), where he simulated cyberattacks on prosthetic arms to study user trust. Additionally, his work on "Robotic Finger Force Sensor Fabrication and Evaluation Through a Glove" (3 citations) advances tactile sensing by integrating Takktile sensors into prosthetic hands. Gonzalez’s interdisciplinary approach—combining robotics, cybersecurity, and human factors—positions him as a key contributor to safer, more intuitive robotic systems.