Jorge Martinez Perez-Tejada
Papers
3
Total Citations
261
H-Index
3
About
Jorge Martinez Perez-Tejada is a pioneering researcher in the field of haptic robotics and human-robot interaction, with a primary focus on enabling robots to learn and communicate through touch. His major contributions center on developing algorithms that allow robots to acquire the meaning of haptic adjectives—such as "soft," "rough," or "smooth"—by physically interacting with objects. Through his landmark 2014 paper, "Robotic learning of haptic adjectives through physical interaction," which has garnered 145 citations, Perez-Tejada demonstrated how robots can use exploratory procedures to build a tactile vocabulary, bridging the gap between raw sensor data and natural language. His 2013 work, with 107 citations, further advanced this concept by showing that robots could autonomously learn word meanings through direct touch, a critical step toward robots that can communicate intuitively with humans. This research delivers on the promise of real-world robotics, where machines must understand and describe their environment as humans do. Perez-Tejada’s work has been foundational in haptic learning, inspiring subsequent studies in robot cognition and sensory linguistics, and his contributions remain essential for developing robots that can seamlessly integrate into human-centered environments.
Research Focus
Key Achievements
Top Papers
- 1Robotic learning of haptic adjectives through physical interaction145 citations · 2014
- 2Using robotic exploratory procedures to learn the meaning of haptic adjectives107 citations · 2013
- 3