Papers
23
Total Citations
395
H-Index
11
About
Chris Messom is a robotics and intelligent systems researcher whose work spans teleoperation, real-time image processing, mobile robot control, and engineering education. He is perhaps best known for his contributions to master-slave teleoperation, with his 2006 paper on anthropomorphic robotic arm control with gripping force sensation accumulating 80 citations — a landmark study demonstrating intuitive, low-cost bilateral control methodologies that bring human-like dexterity to robotic manipulation. Messom's research portfolio reveals a consistent focus on making robots smarter and more responsive. His work on real-time image processing, particularly through run-length encoding (RLE) and Hough transform techniques, provided computationally efficient solutions for robotic vision systems — work that has collectively drawn over 57 citations. His contributions to mobile robot control, including predictive controllers using Kalman filtering and genetic algorithm-based auto-tuning, advanced the field of autonomous robot navigation, notably through the challenging platform of robot soccer. Beyond pure research, Messom has shown a commitment to cultivating the next generation of engineers, with his 2009 paper on robotics competitions in engineering education earning 26 citations. His work on biologically inspired biped balance through sensitive robotic feet further illustrates the breadth and creativity of his research vision, cementing his reputation as a versatile and impactful figure in applied robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Strategy for collaboration in robot soccer35 citations · 2003
- 3
- 4Hough Transform Run Length Encoding for Real-Time Image Processing29 citations · 2007
- 5
- 6Robotics competitions in engineering eduction26 citations · 2009
- 7
- 8
- 9Genetic Algorithms for Auto-tuning Mobile Robot Motion Control16 citations · 2002
- 10Robots with Sensitive Feet15 citations · 2007