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Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation (2020)
Conference Proceeding
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., de Carlo, M., …Tyrrell, A. M. (2020). Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation. In J. Bongard, J. Lovato, L. Hebert-Dufrésne, R. Dasari, & L. Soros (Eds.), Artificial Life Conference Proceedings. , (432-440). https://doi.org/10.1162/isal_a_00299

In evolutionary robot systems where morphologies and controllers of real robots are simultaneously evolved, it is clear that there is likely to be requirements to refine the inherited controller of a ‘newborn’ robot in order to better align it to its... Read More about Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation.

Usability study of a robot companion for monitoring industrial processes (2020)
Conference Proceeding
Sita, E., Thomessen, T., Pipe, A. G., Studley, M., & Dailami, F. (2020). Usability study of a robot companion for monitoring industrial processes. In 2020 5th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS). , (37-42). https://doi.org/10.1109/acirs49895.2020.9162607

In this paper we present the findings of a usability study for a monitoring robotic unit tele-operated via a virtual fixtures (VF) based control framework. The study aims at investigating the impact of VF on the robot navigation as well as the impact... Read More about Usability study of a robot companion for monitoring industrial processes.

Calibration of sound source localisation for robots using multiple adaptive filter models of the cerebellum (2020)
Thesis
Baxendale, M. D. Calibration of sound source localisation for robots using multiple adaptive filter models of the cerebellum. (Thesis). University of the West of England. Retrieved from https://uwe-repository....ribe.com/output/1490813

The aim of this research was to investigate the calibration of Sound Source Localisation (SSL) for robots using the adaptive filter model of the cerebellum and how this could be automatically adapted for multiple acoustic environments. The role of th... Read More about Calibration of sound source localisation for robots using multiple adaptive filter models of the cerebellum.

Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods (2020)
Journal Article
Caleb-Solly, P., Gupta, P., & McClatchey, R. (2020). Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods. Neural Computing and Applications, 32(16), 12351 - 12362. https://doi.org/10.1007/s00521-020-04737-6

© 2020, The Author(s). This paper investigates the utility of unsupervised machine learning and data visualisation for tracking changes in user activity over time. This is done through analysing unlabelled data generated from passive and ambient smar... Read More about Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods.

A corroborative approach to verification and validation of human–robot teams (2019)
Journal Article
Webster, M., Western, D., Araiza-Illan, D., Dixon, C., Eder, K., Fisher, M., & Pipe, A. G. (2020). A corroborative approach to verification and validation of human–robot teams. International Journal of Robotics Research, 39(1), 73-99. https://doi.org/10.1177/0278364919883338

© The Author(s) 2019. We present an approach for the verification and validation (V&V) of robot assistants in the context of human–robot interactions, to demonstrate their trustworthiness through corroborative evidence of their safety and functional... Read More about A corroborative approach to verification and validation of human–robot teams.

Neural network enhanced robot tool identification and calibration for bilateral teleoperation (2019)
Journal Article
Su, H., Yang, C., Mdeihly, H., Rizzo, A., Ferrigno, G., & De Momi, E. (2019). Neural network enhanced robot tool identification and calibration for bilateral teleoperation. IEEE Access, 7, 122041-122051. https://doi.org/10.1109/ACCESS.2019.2936334

© 2013 IEEE. In teleoperated surgery, the transmission of force feedback from the remote environment to the surgeon at the local site requires the availability of reliable force information in the system. In general, a force sensor is mounted between... Read More about Neural network enhanced robot tool identification and calibration for bilateral teleoperation.

Deep neural network approach in human-like redundancy optimization for anthropomorphic manipulators (2019)
Journal Article
Su, H., Qi, W., Yang, C., Aliverti, A., Ferrigno, G., & De Momi, E. (2019). Deep neural network approach in human-like redundancy optimization for anthropomorphic manipulators. IEEE Access, 7, 124207-124216. https://doi.org/10.1109/ACCESS.2019.2937380

© 2013 IEEE. Human-like behavior has emerged in the robotics area for improving the quality of Human-Robot Interaction (HRI). For the human-like behavior imitation, the kinematic mapping between a human arm and robot manipulator is one of the popular... Read More about Deep neural network approach in human-like redundancy optimization for anthropomorphic manipulators.

Onboard Evolution of Understandable Swarm Behaviors (2019)
Journal Article
Jones, S., Winfield, A. F., Hauert, S., & Studley, M. (2019). Onboard Evolution of Understandable Swarm Behaviors. Advanced Science, 1(6), https://doi.org/10.1002/aisy.201900031

Designing the individual robot rules that give rise to desired emergent swarm behaviors is difficult. The common method of running evolutionary algorithms off‐line to automatically discover controllers in simulation suffers from two disadvantages: th... Read More about Onboard Evolution of Understandable Swarm Behaviors.

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.

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.

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.

Enhancing the rate-hardness of haptic interaction: Successive force augmentation approach (2019)
Journal Article
Singh, H., Janetzko, D., Jafari, A., Weber, B., Lee, C. I., & Ryu, J. H. (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

© 1982-2012 IEEE. 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... 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, 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. (2019). Composite learning adaptive backstepping control using neural networks with compact supports. International Journal of Adaptive Control and Signal Processing, 33(12), 1726-1738. https://doi.org/10.1002/acs.3002

© 2019 John Wiley & Sons, Ltd. 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... Read More about Composite learning adaptive backstepping control using neural networks with compact supports.