This research explores why people form emotional bonds with social robots. Through forum analysis and a year-long self-study, it shows that humans transfer emotion to robots and experience reciprocal affect. The work proposes a new framework for understanding human–robot companionship as emotionally co-created, not purely technological.

This thesis introduces Armando, a low-cost soft robotic gripper with proprioceptive sensing using a single flexible capacitive sensor and neural-network decoding. Achieving 99% accuracy, Armando enables precise finger-position estimation for applications in prosthetics, assistive care, and disaster response, advancing accessible tactile robotics inspired by human touch.