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A corroborative approach to verification and validation of human-robot teams (2019)
Journal Article
Webster, M., Western, D., Araiza-Illan, D., Dixon, C., Fisher, M., & Pipe, A. G. (in press). A corroborative approach to verification and validation of human-robot teams. International Journal of Robotics Research, https://doi.org/10.1177/0278364919883338

We present an approach for the verification and validation (V&V) of robot assistants in the context of human-robot interactions (HRI), to demonstrate their trustworthiness through corroborative evidence of their safety and functional correctness. Tru... Read More about A corroborative approach to verification and validation of human-robot teams.

Unknown Dynamics Estimator-Based Output-Feedback Control for Nonlinear Pure-Feedback Systems (2019)
Journal Article
Na, J., Yang, J., Wang, S., Gao, G., & Yang, C. (in press). Unknown Dynamics Estimator-Based Output-Feedback Control for Nonlinear Pure-Feedback Systems. IEEE Transactions on Systems Man and Cybernetics: Systems, 1-12. https://doi.org/10.1109/tsmc.2019.2931627

Most existing adaptive control designs for nonlinear pure-feedback systems have been derived based on backstepping or dynamic surface control (DSC) methods, requiring full system states to be measurable. The neural networks (NNs) or fuzzy logic syste... Read More about Unknown Dynamics Estimator-Based Output-Feedback Control for Nonlinear Pure-Feedback Systems.

Neural adaptive global stability control for robot manipulators with time-varying output constraints (2019)
Journal Article
Fan, Y., Kang, T., Wang, W., & Yang, C. (2019). Neural adaptive global stability control for robot manipulators with time-varying output constraints. International Journal of Robust and Nonlinear Control, 29(16), 5765-5780. https://doi.org/10.1002/rnc.4690

© 2019 John Wiley & Sons, Ltd. In this paper, a novel adaptive control scheme is proposed based on radial basis function neural network (RBFNN). The considered system is deduced by the structure of RBFNN with nonzero time-varying parameter that ins... Read More about Neural adaptive global stability control for robot manipulators with time-varying output constraints.

Requirements elicitation for robotic and computer-assisted minimally invasive surgery (2019)
Journal Article
Nakawala, H., De Momi, E., Tzemanaki, A., Dogramadzi, S., Russo, A., Catellani, M., …Ferrigno, G. (2019). Requirements elicitation for robotic and computer-assisted minimally invasive surgery. International Journal of Advanced Robotic Systems, 16(4), 172988141986580. https://doi.org/10.1177/1729881419865805

The robotic surgical systems and computer-assisted technologies market has seen impressive growth over the last decades, but uptake by end-users is still scarce. The purpose of this article is to provide a comprehensive and informed list of the end-u... Read More about Requirements elicitation for robotic and computer-assisted minimally invasive surgery.

Temporal patterns in multi-modal social interaction between elderly users and service robot (2019)
Journal Article
Wang, N., Di Nuovo, A., Cangelosi, A., & Jones, R. (2019). Temporal patterns in multi-modal social interaction between elderly users and service robot. Interaction Studies, 20(1), 4-24. https://doi.org/10.1075/is.18042.wan

Social interaction, especially for older people living alone is a challenge currently facing human-robot interaction (HRI). There has been little research on user preference towards HRI interfaces. In this paper, we took both objective observations a... Read More about Temporal patterns in multi-modal social interaction between elderly users and service robot.

Toward controllable morphogenesis in large robot swarms (2019)
Journal Article
Hauert, S., Carrillo-Zapata, D., Sharpe, J., Winfield, A. F. T., & Giuggioli, L. (2019). Toward controllable morphogenesis in large robot swarms. IEEE Robotics and Automation Letters, 4(4), 3386-3393. https://doi.org/10.1109/LRA.2019.2926961

Morphogenetic engineering aims to achieve functional, self-organized but controllable structures in human-designed systems. Controlling the structures is crucial if they are to be used for real-world applications. Building on previous work on morphog... Read More about Toward controllable morphogenesis in large robot swarms.

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. (2020). Enhancing the rate-hardness of haptic interaction: Successive force augmentation approach. IEEE Transactions on Industrial Electronics, 67(1), 809-819. 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 about Enhancing the rate-hardness of haptic interaction: Successive force augmentation approach.

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 about New noise-tolerant neural algorithms for future dynamic nonlinear optimization with estimation on hessian matrix inversion.

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 about Enhancing the force transparency of time domain passivity approach: Observer-based gradient controller.

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 about Composite learning adaptive backstepping control using neural networks with compact supports.

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 about Adaptive neural network control of underactuated surface vessels with guaranteed transient performance: Theory and experimental results.

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 about A task learning mechanism for the telerobots.

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 about Force sensorless admittance control with neural learning for robots with actuator saturation.

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 about On the simulation (and energy costs) of human intelligence, the singularity and simulationism.

Characterisation of a nuclear cave environment utilising an autonomous swarm of heterogeneous robots (2019)
Thesis
Bridgwater, T. J. F. Characterisation of a nuclear cave environment utilising an autonomous swarm of heterogeneous robots. (Thesis). University of the West of England and University of Bristol. Retrieved from https://uwe-repository....ribe.com/output/1490801

As nuclear facilities come to the end of their operational lifetime, safe decommissioning becomes a more prevalent issue. In many such facilities there exist ‘nuclear caves’. These caves constitute areas that may have been entered infrequently, or ev... Read More about Characterisation of a nuclear cave environment utilising an autonomous swarm of heterogeneous robots.

Designing bio-inspired robotics workshops given language limitations (2019)
Presentation / Conference
Carrillo-Zapata, D., Lee, C., Digumarti, K. M., Hauert, S., & Boushel, C. (2019, April). Designing bio-inspired robotics workshops given language limitations. Paper presented at RiE 2019 : 10th International Conference on Robotics in Education

Educational robots are increasingly being used in schools as learning tools to support the development of skills such as computational thinking because of the growing number of technology-related jobs. Using robots as a tool inside the classroom has... Read More about Designing bio-inspired robotics workshops given language limitations.

Asymmetric bounded neural control for an uncertain robot by state feedback and output feedback (2019)
Journal Article
Kong, L., He, W., Dong, Y., Cheng, L., Yang, C., & Li, Z. (in press). Asymmetric bounded neural control for an uncertain robot by state feedback and output feedback. IEEE Transactions on Systems Man and Cybernetics: Systems, 1-12. https://doi.org/10.1109/TSMC.2019.2901277

In this paper, an adaptive neural bounded control scheme is proposed for an n-link rigid robotic manipulator with unknown dynamics. With the combination of the neural approximation and backstepping technique, an adaptive neural network control policy... Read More about Asymmetric bounded neural control for an uncertain robot by state feedback and output feedback.