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About

Benjamin A. Richardson is a prominent researcher at the intersection of haptics, machine learning, and robotic perception, with a particular focus on how machines can replicate the sophisticated sense of touch that humans possess. His work addresses a fundamental challenge in robotics and AI: enabling systems to understand and interpret tactile information with the nuance and richness of human perception. Richardson's most influential contribution, "Learning to Feel Textures" (2022, 27 citations), investigates how the brain constructs abstract representations of surface textures from complex finger-surface dynamics — a question with profound implications for both neuroscience and robotics. Building on this foundation, his earlier work on haptic adjective recognition (2019, 20 citations) pioneered unsupervised feature learning approaches to give robots human-like descriptive tactile intelligence, moving beyond brittle hand-crafted features. His 2020 paper further advanced the field by modeling the subjective variability inherent in human tactile perception. More recently, Richardson has expanded into multimodal sensory fusion, combining vision, touch, and audio for in-hand object pose estimation and fabric recognition using soft robotic fingertips. Together, his body of work — accumulating over 65 citations — is systematically building the perceptual foundations needed for truly dexterous, touch-aware robotic systems.