Research Repository

See what's under the surface


An accuracy-based fuzzy classifier system (2019)
Presentation / Conference
Casillias, J., Carse, B., & Bull, L. (2019, June). An accuracy-based fuzzy classifier system. Paper presented at 12th Spanish Conference on Fuzzy Logic and Technologies

The nose on your face may not be so plain: Using the nose as a biometric (2019)
Presentation / Conference
Moorhouse, A., Evans, N., Atkinson, G., Sun, J., & Smith, M. (2019, June). The nose on your face may not be so plain: Using the nose as a biometric. Paper presented at International Conference on Imaging for Crime Detection and Prevention, Kingston-Upon-Thames, London, UK 2009

Evolving spiking networks with variable memristors (2019)
Presentation / Conference
Howard, G. D., Gale, E., Bull, L., de Lacy Costello, B., & Adamatzky, A. (2019, June). Evolving spiking networks with variable memristors. Paper presented at 13th annual conference on Genetic and evolutionary computation

The photoface database (2019)
Presentation / Conference
Zafeirou, S., Hansen, M. F., Atkinson, G., Argyriou, V., Petrou, M., Smith, M., & Smith, L. (2019, June). The photoface database. Paper presented at Biometrics Workshop of Computer Vision and Pattern Recognition

Concealed object perception and recognition using a photometric stereo strategy (2019)
Presentation / Conference
Sun, J., Smith, M., Farooq, A., & Smith, L. (2019, June). Concealed object perception and recognition using a photometric stereo strategy. Paper presented at Advanced Concepts for Intelligent Vision Systems

Following a review of current hidden objects detection techniques in a range of security applications, a strategy based on an innovative, low-cost photometric stereo technique is proposed to reveal concealed objects. By taking advantage of informatio... Read More

Enhancing the rate-hardness of haptic interaction: Successive force augmentation approach (2019)
Journal Article
Singh, H., Janetzko, D., Jafari, A., Weber, B., Lee, C., & Ryu, J. (in press). Enhancing the rate-hardness of haptic interaction: Successive force augmentation approach. IEEE Transactions on Industrial Electronics, https://doi.org/10.1109/TIE.2019.2918500

There have been numerous approaches that have been proposed to enlarge the impedance range of haptic interaction while maintaining stability. However, enhancing the rate-hardness of haptic interaction while maintaining stability is still a challengin... Read More

New noise-tolerant neural algorithms for future dynamic nonlinear optimization with estimation on hessian matrix inversion (2019)
Journal Article
Wei, L., Jin, L., Yang, C., Chen, K., & Li, W. (in press). New noise-tolerant neural algorithms for future dynamic nonlinear optimization with estimation on hessian matrix inversion. IEEE Transactions on Systems Man and Cybernetics: Systems, 1-13. https://doi.org/10.1109/TSMC.2019.2916892

Nonlinear optimization problems with dynamical parameters are widely arising in many practical scientific and engineering applications, and various computational models are presented for solving them under the hypothesis of short-time invariance. To... Read More

Enhancing the force transparency of time domain passivity approach: Observer-based gradient controller (2019)
Presentation / Conference
Singh, H., Jafari, A., & Ryu, J. (2019, May). Enhancing the force transparency of time domain passivity approach: Observer-based gradient controller. Paper presented at The 2019 International Conference on Robotics and Automation (ICRA)

Passivity has been the most often used constraint for the stable controller design of bilateral teleoperation systems. Especially, Time Domain Passivity Approach (TDPA) has been used in many applications since it has been known as one of the least co... Read More

Composite learning adaptive backstepping control using neural networks with compact supports (2019)
Journal Article
Pan, Y., Yang, C., Pratama, M., & Yu, H. (in press). Composite learning adaptive backstepping control using neural networks with compact supports. International Journal of Adaptive Control and Signal Processing, https://doi.org/10.1002/acs.3002

The ability to learn is crucial for neural network (NN) control as it is able to enhance the overall stability and robustness of control systems. In this study, a composite learning control strategy is proposed for a class of strict-feedback nonlinea... Read More

Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results (2019)
Journal Article
Chen, L., Cui, R., Yang, C., & Yan, W. (in press). Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results. IEEE Transactions on Industrial Electronics, 1-1. https://doi.org/10.1109/TIE.2019.2914631

In this paper, an adaptive trajectory tracking control algorithm for underactuated unmanned surface vessels (USVs) with guaranteed transient performance is proposed. To meet the realistic dynamical model of USVs, we consider that the mass and dam... Read More

Does the D.C. response of memristors allow robotic short-term memory and a possible route to artificial time perception? (2019)
Presentation / Conference
Gale, E., de Lacy Costello, B., & Adamatzky, A. (2019, May). Does the D.C. response of memristors allow robotic short-term memory and a possible route to artificial time perception?. Paper presented at Workshop Unconventional Approaches to Robotics, Automation and Control Inspired by Nature (UARACIN) in:

Time perception is essential for task switching, and in the mammalian brain appears alongside other processes. Memristors are electronic components used as synapses and as models for neurons. The d.c. response of memristors can be considered as a typ... Read More

A task learning mechanism for the telerobots (2019)
Journal Article
Luo, J., Yang, C., Li, Q., & Wang, M. (in press). A task learning mechanism for the telerobots. International Journal of Humanoid Robotics, 1950009. https://doi.org/10.1142/S0219843619500099

Telerobotic systems have attracted growing attention because of their superiority in the dangerous or unknown interaction tasks. It is very challengeable to exploit such systems to implement complex tasks in an autonomous way. In this paper, we prop... Read More

Force sensorless admittance control with neural learning for robots with actuator saturation (2019)
Journal Article
Peng, G., Yang, C., He, W., & Chen, C. L. P. (in press). Force sensorless admittance control with neural learning for robots with actuator saturation. IEEE Transactions on Industrial Electronics, 1-1. https://doi.org/10.1109/TIE.2019.2912781

In this paper, we present a sensorless admittance control scheme for robotic manipulators to interact with unknown environments in the presence of actuator saturation. The external environment are defined as linear models with unknown dynamics. Usi... Read More

On the simulation (and energy costs) of human intelligence, the singularity and simulationism (2019)
Book Chapter
Winfield, A. F. T. (2019). On the simulation (and energy costs) of human intelligence, the singularity and simulationism. In A. Adamatzky, & V. Kendon (Eds.), From Astrophysics to Unconventional Computation, 397-407. Springer Nature Publishing AG. https://doi.org/10.1007/978-3-030-15792-0_16

For many the Holy Grail of robotics and AI is the creation of artificial persons: artefacts with equivalent general competencies as humans. Such artefacts would literally be simulations of humans. With the theme of simulation this essay reflects on b... Read More