Prof Chenguang (Charlie) Yang, PhD, CEng
Fellow of IEEE, IET, IMechE, BCS, AAIA & HEA
Member of European Academy of Sciences and Arts
Head of Robotics and Autonomous Systems Group
Department of Computer Science
University of Liverpool
Liverpool, L69 3BX, UK
chenguang.Yang@liverpool.ac.uk
Title: Robot Control by Learning from Humans
Abstract: This presentation will provide a broad overview of my research in robotics with a focus on learning from Demonstration (LfD). LfD allows robots to acquire and generalize task skills through human demonstrations, creating a seamless integration of artificial intelligence and robotics. Most LfD approaches often overlook the importance of demonstrated forces and rely on manually configured impedance parameters. In response, my team has developed a series of biomimetic impedance and force controllers inspired by neuroscientific findings on motor control mechanisms in humans, enabling robots to imitate compliant manipulation skills. The presentation also covers collaborative control strategies for human-robot interaction, and long-horizon manipulation based on subgoal planning. Tactile sensing designs, soft gripper designs, perception and mapping methods, and advancements in dynamic SLAM and object tracking are also included. Particularly, we designed anthropomorphic visual tactile sensors that assess contact force, surface texture, and shape, to improve robot skill learning through enhanced perceptual capabilities.
Professor Mark Hansen
Centre for Machine Vision, Bristol Robotics Lab
School of Engineering
University of the West of England, Bristol, UK
Mark.Hansen@uwe.ac.uk
Title: Machine vision for real-world applications
Abstract: The vast expansion of the existed loads besides the rapid increase of deploying the renewable energy resources have created many challenges for the power system operators to control and maintain the energy demand. The increase of the volatility of the energy prices has initiated obstacles to manage the energy usage. Therefore, demand response (DR) programs is designed in the modern electricity markets to overcome these challenges and smooth the management of the load patterns. Also, the DR allows the power system operator to effectively interact with the end-user costumers to reduce or change the demand according to the availability of the power productions. The lecture will describe how the DR has the ability to deal with various bidding prices and the power systems鈥� technical constraints to ensure both the energy balance and the minimum operation costs. The lecture also aims to describe the technique of the DR to procure the minimum operation costs of a power network through advanced optimization technique. Examples and case studies will be discussed to demonstrate the effectiveness of applying the DR in the electricity markets.
Biography: Mark Hansen is a Professor of Machine Vision and Machine learning in the Centre for Machine Vision at the Bristol Robotics Laboratory, UWE Bristol. He has a very wide range of experience with a BSc Psychology, an MSc Computer Science and 10 years in the software engineering industry before completing an engineering PhD. For the last decade his work has focussed primarily on Agritech and precision livestock farming, with three commercialisations (HarvestEye, Herd.vision, SKAi reconfigurable camera) as well as fundamental research on pig biometrics/welfare recognition and automated mealworm farming. He has around 40 publications and currently supervises 6 PhD students. He is particularly driven by translating state-of-the-art research into useable on-farm applications and is an Associate Editor for Elsevier's Computers and Electronics in Agriculture.
Dr Khalid Alqunun
department of electrical engineering
University of Hail, Saudi Arabia
Kh.ALqunun@uoh.edu.sa
Title: The Role of Demand Response in Modern Electricity Markets: Challenges and Opportunities
Abstract: The vast expansion of the existed loads besides the rapid increase of deploying the renewable energy resources have created many challenges for the power system operators to control and maintain the energy demand. The increase of the volatility of the energy prices has initiated obstacles to manage the energy usage. Therefore, demand response (DR) programs is designed in the modern electricity markets to overcome these challenges and smooth the management of the load patterns. Also, the DR allows the power system operator to effectively interact with the end-user costumers to reduce or change the demand according to the availability of the power productions. The lecture will describe how the DR has the ability to deal with various bidding prices and the power systems鈥� technical constraints to ensure both the energy balance and the minimum operation costs. The lecture also aims to describe the technique of the DR to procure the minimum operation costs of a power network through advanced optimization technique. Examples and case studies will be discussed to demonstrate the effectiveness of applying the DR in the electricity markets.
Biography: Khalid Alqunun received the M.Sc. degree in electrical engineering from the University of Denver, Colorado, in 2014, and the Ph.D degree in the electrical and electronic engineering from the University of Manchester, U.K., in 2017. He is currently an Associate Professor in the department of electrical engineering at the University of Hail, Saudi Arabia. His main research interests include power system optimization, energy economics and operation of renewable energy resources.
Ahmed CHEMORI
IEEE Senior Member
Robotics Department
LIRMM, University of Montpellier, CNRS
161, rue Ada, Montpellier, France
Ahmed.Chemori@lirmm.fr
Title: Control Issues & Some Solutions for High-Speed Industrial Applications of PKMs
Abstract: Serial robotic manipulators are mainly characterized by their large workspace and their high dexterity. However, despite these advantages, to perform tasks requiring high speeds/accelerations and/or high precision; such robots are not always recommended because of their lack of stiffness and accuracy. Indeed, parallel kinematic manipulators (PKMs) are more suitable for such tasks. The main idea of their mechanical structure consists in using at least two kinematic chains linking the fixed base to the travelling plate, where each of these chains contains at least one actuator. This may allow a good distribution of the load between the chains. PKMs have important advantages with respect to their serial counterparts in terms of stiffness, speed, accuracy and payload. However, these robots are characterized by their high nonlinear dynamics, kinematic redundancy, uncertainties, actuation redundancy, singularities, etc. Besides, when interested in high-speed robotized tasks, such as food packaging and waste sorting applications, the key idea lies in looking for short cycle-times. This means obviously to look for short motion and short stabilization times while guaranteeing robustness and performance with respect to disturbances and changes/uncertainties in the operational conditions. Consequently, if we are interested in controlling such robots, all these issues should be considered, which makes it a bit challenging task. This talk will give an overview of some proposed advanced control solutions for high-speed industrial applications of PKMs in food packaging, waste sorting, and machining tasks. The proposed solutions are mainly borrowed from nonlinear robust, adaptive, or predictive control techniques and have been validated through real-time experiments on different PKM prototypes.
Biography: Ahmed CHEMORI received his M.Sc. and Ph.D. degrees, both in automatic control from Polytechnic Institute of Grenoble, France, in 2001 and 2005 respectively. In 2004/2005 he has been a Research and Teaching assistant at L2S laboratory, University Paris 11. Then he joined Gipsa-Lab as a CNRS postdoctoral researcher. He is currently a senior CNRS researcher in Automatic control and Robotics at LIRMM Laboratory. His research interests include nonlinear (robust, adaptive and predictive) control and their real-time applications in different fields of robotics (underwater robotics, parallel robotics, wearable robotics, and underactuated robotics). He is the author of nearly 200 scientific publications, including international journals, patents, books, book chapters and international conferences. He is currently Technical Editor of the Journal IEEE/ASME Transactions on Mechatronics and served as guest editor for several special issues in other journals. He is member of the IFAC Technical Committee on Adaptive and Learning Systems (TC 1.2), the IFAC Technical Committee on Mechatronic Systems (TC 4.2), the IFAC Technical Committee on Robotics (TC 4.3), and the IFAC Technical Committee on Marine Systems (TC 7.2). He served as a TPC/IPC member or associate editor for different international conferences and organized