Ian Stott

University of Portsmouth, English Heritage

Papers

Total Citations

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About

Ian Stott is a researcher whose work sits at the intersection of robotics, human-machine interaction, and intelligent control systems. His research has focused primarily on improving the effectiveness and safety of tele-operated mobile robots, exploring how operator interfaces and decision-support tools influence performance outcomes in complex environments. Stott's most impactful contributions examine the practical challenges facing human tele-operators working with mobile robots. In a widely cited 2011 study (31 citations), he investigated how different modes of tele-operation affect failure rates, revealing critical insights into how operator interaction styles influence navigation through increasingly demanding environments. Complementing this, his equally influential work on expert systems (30 citations) demonstrated how simple, intelligent interpretation of joystick and sensor data could meaningfully reduce operator workload and reliance on visual feedback alone — a significant step toward more accessible and reliable remote robotics. His earlier work from 1994 explored the application of neural networks as both feedforward estimators and feedback controllers for robotic systems, reflecting a long-standing interest in intelligent, adaptive control architectures. Together, Stott's research offers a coherent body of work addressing real-world limitations in tele-robotics, making his findings particularly valuable to engineers and researchers designing human-centered robotic systems for challenging operational settings.