Outputs (73)

Imitation learning for coordinated human–robot collaboration based on hidden state-space models (2022)
Journal Article
Wang, L., Wang, G., Jia, S., Turner, A., & Ratchev, S. (2022). Imitation learning for coordinated human–robot collaboration based on hidden state-space models. Robotics and Computer-Integrated Manufacturing, 76, Article 102310. https://doi.org/10.1016/j.rcim.2021.102310

This paper proposes a novel coordinated human–robot collaboration framework based on the hidden state-space model, which probabilistically clones the human behaviour and presents dynamic features in a nonparametric form. Derived from the filter predi... Read More about Imitation learning for coordinated human–robot collaboration based on hidden state-space models.

An efficient cost estimation framework for aerospace applications using Matlab/Simulink (2021)
Presentation / Conference Contribution
Bacharoudis, K., Wilson, H., Goodfellow-Jones, S., Popov, A., & Ratchev, S. An efficient cost estimation framework for aerospace applications using Matlab/Simulink. Presented at 54th CIRP Conference on Manufacturing Systems, 2021, Online

The ability to estimate costs and process times at the early stage of a design phase is of great importance to the product development process, enabling selection of the most suitable design and manufacturing concepts. Therefore, herein an efficient... Read More about An efficient cost estimation framework for aerospace applications using Matlab/Simulink.

Application of Multi Agent Systems for Leak Testing (2021)
Presentation / Conference Contribution
Rehman, H. U., Chaplin, J. C., Zarzycki, L., Jones, M., & Ratchev, S. (2021, November). Application of Multi Agent Systems for Leak Testing. Presented at 2021 9th International Conference on Systems and Control (ICSC), Caen, France

The manufacturing of customised products is a driver in the trend of incorporating intelligence in the system. This intelligence is required to enable the system to self-conFigure processes to meet the requirements of unique products. This work deals... Read More about Application of Multi Agent Systems for Leak Testing.

Visualisation on a Shoestring: a low-cost approach for building visualisation components of industrial digital solutions (2021)
Presentation / Conference Contribution
Martínez-Arellano, G., McNally, M. J., Chaplin, J. C., Ling, Z., McFarlane, D., & Ratchev, S. (2021, November). Visualisation on a Shoestring: a low-cost approach for building visualisation components of industrial digital solutions. Presented at 11th International Workshop on Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future (SOHOMA’21), Cluny, France

The rate of adoption of digital solutions in manufacturing environments remains low despite the benefits these can bring. This is particularly acute among industrial small and medium enterprises (SMEs), who typically do not have the confidence to ado... Read More about Visualisation on a Shoestring: a low-cost approach for building visualisation components of industrial digital solutions.

Enhancing learning capabilities of movement primitives under distributed probabilistic framework for flexible assembly tasks (2021)
Journal Article
Wang, L., Jia, S., Wang, G., Turner, A., & Ratchev, S. (2021). Enhancing learning capabilities of movement primitives under distributed probabilistic framework for flexible assembly tasks. Neural Computing and Applications, 35(32), 23453-23464. https://doi.org/10.1007/s00521-021-06543-0

This paper presents a novel probabilistic distributed framework based on movement primitives for flexible robot assembly. Since the modern advanced industrial cell usually deals with various scenarios that are not fixed via-point trajectories but hig... Read More about Enhancing learning capabilities of movement primitives under distributed probabilistic framework for flexible assembly tasks.

Cloud Based Decision Making for Multi-Agent Production Systems (2021)
Presentation / Conference Contribution
Rehman, H. U., Pulikottil, T., Estrada-Jimenez, L. A., Mo, F., Chaplin, J. C., Barata, J., & Ratchev, S. (2021, September). Cloud Based Decision Making for Multi-Agent Production Systems. Presented at EPIA2021 - 20th EPIA Conference on Artificial Intelligence, [Online]

The use of multi-agent systems (MAS) as a distributed control method for shop-floor manufacturing control applications has been extensively researched. MAS provides new implementation solutions for smart manufacturing requirements such as the high dy... Read More about Cloud Based Decision Making for Multi-Agent Production Systems.

Feedforward Enhancement through Iterative Learning Control for Robotic Manipulator (2021)
Presentation / Conference Contribution
Liu, C., Wang, M., Li, X., & Ratchev, S. (2021, August). Feedforward Enhancement through Iterative Learning Control for Robotic Manipulator. Presented at IEEE 17th International Conference on Automation Science and Engineering, Lyon, France

This work presents an iterative learning control (ILC) algorithm to enhance the feedforward control (FFC) for robotic manipulators. The proposed ILC algorithm enables the cooperation between the ILC, inverse dynamics, and a PD feedback control (FBC)... Read More about Feedforward Enhancement through Iterative Learning Control for Robotic Manipulator.

A Framework for Self-Configuration in Manufacturing Production Systems (2021)
Presentation / Conference Contribution
Rehman, H. U., Chaplin, J. C., Zarzycki, L., & Ratchev, S. (2021, July). A Framework for Self-Configuration in Manufacturing Production Systems. Presented at 12th Advanced Doctoral Conference On Computing, Electrical And Industrial Systems (DOCEIS2021), Caparica, Portugal

Intelligence in manufacturing enables the optimization and configuration of processes, and a goal of future smart manufacturing is to enable processes to configure themselves-called self-configuration. This paper describes a framework for utilising d... Read More about A Framework for Self-Configuration in Manufacturing Production Systems.

Learning Feedforward Control for Industrial Manipulators (2021)
Presentation / Conference Contribution
Liu, C., Popov, A., Turner, A., Shires, E., & Ratchev, S. (2021, May). Learning Feedforward Control for Industrial Manipulators. Presented at IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS 2021), Suzhou, China

In this work, an iterative learning control (ILC) algorithm is proposed for industrial manipulators. The proposed ILC algorithm works coordinately with the inverse dynamics of the manipulator and a feedback controller. The entire control scheme has t... Read More about Learning Feedforward Control for Industrial Manipulators.

Context-Aware Plug and Produce for Robotic Aerospace Assembly (2021)
Presentation / Conference Contribution
Sanderson, D., Shires, E., Chaplin, J. C., Brookes, H., Liaqat, A., & Ratchev, S. (2020, December). Context-Aware Plug and Produce for Robotic Aerospace Assembly. Presented at IPAS 2020: 9th International Precision Assembly Seminar, Kitzbühel, Austria

Aerospace production systems face increasing requirements for flexibility and reconfiguration, along with considerations of cost, utilisation, and efficiency. This drives a need for systems with a small number of automation platforms (e.g. industrial... Read More about Context-Aware Plug and Produce for Robotic Aerospace Assembly.