Papers
22
Total Citations
376
H-Index
8
About
Robert Lowe is a researcher specializing in affective computing, human-robot interaction (HRI), and embodied cognitive architectures, with a particular focus on how emotion and motivation can be meaningfully integrated into robotic systems. His most influential work, "Affective Touch in Human–Robot Interaction" (2017, 134 citations), pioneered the study of tactile emotional communication with the Nao robot, establishing a landmark framework for conveying both positive and negative emotions through touch. His foundational theoretical contribution, "On the Role of Emotion in Embodied Cognitive Architectures" (2009, 112 citations), has shaped how researchers conceptualize emotional processing in artificial agents. Lowe's research spans an impressive breadth — from biologically inspired models of artificial metabolism and homeostatic motivation to neurocomputational models of fear conditioning and reinforcement learning using nociceptive signals. His work consistently bridges neuroscience, cognitive science, and robotics, translating biological principles into functioning robotic architectures. More recently, his research has extended into deep learning approaches for detecting user engagement in HRI contexts. Across his career, Lowe has made enduring contributions to the understanding of how robots can be designed to feel, learn, and interact in emotionally meaningful ways.
Research Focus
Key Achievements
Top Papers
- 1Affective Touch in Human–Robot Interaction: Conveying Emotion to the Nao Robot134 citations · 2017
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- 3Grounding Motivation in Energy Autonomy: A Study of Artificial Metabolism Constrained Robot Dynamics18 citations · 2010
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- 8Utilizing Emotions in Autonomous Robots: An Enactive Approach8 citations · 2014
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