Michael Arrigo

Papers

Total Citations

261

H-Index

About

Michael Arrigo is a leading researcher in haptic robotics and human-robot interaction, whose work focuses on enabling robots to learn and communicate through physical touch. His key contributions center on developing robotic systems that can understand and use haptic adjectives—words like "soft," "rough," or "smooth"—by directly interacting with objects. In his seminal 2014 paper, "Robotic learning of haptic adjectives through physical interaction" (145 citations), Arrigo demonstrated how robots could autonomously explore surfaces using exploratory procedures and map tactile sensations to linguistic labels. This was built upon his earlier 2013 work, "Using robotic exploratory procedures to learn the meaning of haptic adjectives" (107 citations), which laid the groundwork for robots to acquire vocabulary through real-world experience rather than pre-programmed definitions. Arrigo’s research is pivotal in bridging the gap between physical sensing and natural language, promising a future where robots can communicate tactile experiences intuitively. His work has been widely cited in robotics, AI, and cognitive science communities, influencing how machines learn from their environment. By tackling the challenge of grounding language in physical interaction, Arrigo has advanced the vision of robots that can learn and adapt through everyday touch.