Colin G. Johnson

About

Colin G. Johnson is a versatile computer scientist whose research spans robotics, artificial intelligence, and bio-inspired computing. He is perhaps best known for his pioneering work on emotion-driven robot learning, most notably the development of the Situation-Aware FEar Learning (SAFEL) model, which draws on neuroscientific understanding of the brain's fear-conditioning mechanisms to enable companion robots to anticipate and respond to threatening situations. This influential line of work, which has accumulated 25 citations and spawned several follow-up studies, reflects Johnson's broader interest in building cognitively plausible architectures for robot companions that integrate emotional and contextual awareness. Beyond affective robotics, Johnson has made significant contributions to autonomous navigation, applying Max-Min Ant System and Ant Colony Optimization algorithms to exploratory path planning in both static and dynamic environments. His earlier work in the late 1990s and early 2000s on modelling robot manipulators using multivariate B-splines helped lay groundwork for more intuitive CAD-based robot programming. He has also contributed to evolutionary computation through research on Genetic Programming with Guaranteed Constraints. Across these diverse areas, Johnson's work reflects a consistent drive to make autonomous systems more intelligent, adaptable, and biologically grounded, earning him a solid and growing citation record across multiple research communities.

Research Focus

Key Achievements

Top Papers

1. 1
   A Situation-Aware Fear Learning (SAFEL) model for robots

   25 citations · 2016
2. 2
   Exploratory path planning using the Max-min ant system algorithm

   15 citations · 2016
3. 3
   Modelling robot manipulators with multivariate B-splines

   12 citations · 1999
4. 4
   Genetic Programming with Guaranteed Constraints

   12 citations · 2004
5. 5
   An architecture for emotional and context-aware associative learning for robot companions

   9 citations · 2015
6. 6
   Exploratory path planning for mobile robots in dynamic environments with ant colony optimization

   8 citations · 2020
7. 7
   Modelling robot manipulators in a CAD environment using B-splines

   7 citations · 2002
8. 8
   Fear Learning for Flexible Decision Making in RoboCup: A Discussion

   5 citations · 2018
9. 9
   Improving the predictive performance of SAFEL: A Situation-Aware FEar Learning model

   4 citations · 2016
10. 10
    An Artificial Synaptic Plasticity Mechanism for Classical Conditioning with Neural Networks

    4 citations · 2014

Key Collaborators

Contact & Links