Joe Collenette

Papers

Total Citations

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About

Joe Collenette’s research sits at the intersection of artificial intelligence, robotics, and human-robot interaction, with a particular focus on endowing machines with social and emotional intelligence. His most cited work, “Modelling Mood in Co-operative Emotional Agents” (2018, 6 citations), introduces a framework for simulating affective states in autonomous agents, enabling more natural and adaptive cooperation in multi-agent systems—a foundational step toward emotionally aware robotics. In “Towards Robots for Social Engagement” (2017, 2 citations), Collenette explores design principles for robots capable of meaningful social interaction, addressing challenges in perception and response that are critical for applications in healthcare, education, and domestic assistance. His more recent paper, “Multi-agent Control of Industrial Robot Vacuum Cleaners” (2020, 2 citations), demonstrates a practical application of distributed control algorithms, bridging theoretical multi-agent coordination with real-world industrial tasks. While his citation counts reflect an emerging career, Collenette’s work is notable for its forward-looking integration of emotional modelling into robotic systems, a direction that promises to reshape how robots collaborate with humans and each other. His contributions are particularly relevant for students and researchers interested in affective computing, social robotics, and the future of autonomous systems.