Dr. Haitham Hussien
School of Science, Engineering and Environment
Senior Research Fellow in Soft Robotics
Haitham Hussien received his MSc and PhD degrees in Mechatronics and Robotics Engineering from Egypt-Japan University of Science and Technology (E-JUST) in 2013 and 2016, respectively. Since completing his PhD, Haitham has worked as an Assistant Professor of Robotics Engineering at the Faculty of Engineering at Benha University in Egypt. During 2017, he has held a post of a postdoctoral researcher at KOREATECH University in South Korea in collaboration with Stanford University. He was involved as a contributor to a joint US-Korea research project on Human-Centered Design and Control of Vine Robots for Disaster Scenarios, funded by the Department of Defense (DoD) of the US and the National Research Foundation (NRF) of Soth Korea. Since August 2019, Haitham has taken up a post of Senior Research Fellow in Soft Robotics at the Centre for Autonomous Systems & Advanced Robotics at the University of Salford in Manchester, UK. His research expertise includes soft robotics, soft haptics, teleoperation, human-robot interaction and applied intelligence.
Areas of research
Robotics, Soft robots, Human-Robot Interaction, Artificial Intelligence and Predictive Control
Areas of supervision
Soft Robotics, Reinforcement Learning, Machine Learning, Teleoperation
Learning by demonstration of Soft Robotics:
Recently, continuum flexible robots have been designed for the use in diverse applications; including the exploration of confined static and dynamic environments. One of the challenging tasks for those robots is planning optimal trajectories due to, not only the redundant Degrees of Freedom (DOF) they own but also their compliant behaviour. In this paper, an Imitation-based Pose Planning (IbPP) approach is proposed to teach a two-section continuum robot the motion primitives that will facilitate achieving and generalizing for spatial point-to-point motion which involves both position and orientation goals encoded in a dual quaternion form. Two novel approaches are proposed in this research to intuitively generate the motion demonstrations that will be used in the proposed IbPP. Namely, a flexible input interface, acting as a twin robot, is designed to allow a human to demonstrate different motions for the robot end-effector. Alternatively, as a second approach, the Microsoft Kinect sensor is used to provide motion demonstrations faster via human arm movements. Based on the kinematic model of the two-section continuum robot, a Model Reference Adaptive Control (MRAC) algorithm is developed to achieve tracking the generated trajectory from the IbPP and to guarantee the robustness against the model uncertainties and external disturbances. Moreover, controller stability analysis is developed based on Lyapunov criteria. Finally, simulations are conducted for the two-section continuum robot to prove the ability of the proposed IbPP with the two proposed inputs to learn and generalize for spatial motions, which in future could be easily accommodated for robots with multiple sections. In addition, the proposed MRAC shows a significant performance towards following the required trajectory and rejecting the external disturbance.
Soft Robotics for Assistance of Patients with Neurological Motor Diseases:
Motor neurone disease (MND) is a devastating neurodegenerative condition affecting 2-4 individuals per 100 000 population per year, with a slightly higher incidence in men; unfortunately, most patients with this condition will die in the first 2 or 3 years.
The aim of the project is it develop assistive solutions which will optimise a patient’s function and independence, during this drastically shortened life journey. Specifically, tools that assist with upper limb function thus improving patient ability to carry out daily activities and ultimately enable them to maintain some independence for as long as possible, positively impacting their general wellbeing and ability to live with their illness
In addition to impacting on speech, swallowing and respiratory difficulties; MND will often affect more than one region of the body with either one or both limbs affected. These deficits will have a significant impact on the patient’s ability to carry out activities of daily living and ultimately on their quality of life. This in turn will also have burdensome effect on the patient’s carer.
- 2013 – 2016 Ph.D. in Mechatronics and Robotics Engineering E-JUST, Egypt
Title: Development of a Cognitive Human-Robot Interaction System for Dexterous Teleoperation
- 2011 – 2013 M.Sc. in Mechatronics and Robotics Engineering E-JUST, Egypt
Title: Improving Robots Exploration by Heuristic Backtracking in Sensor-based Techniques.
- 2002 – 2007 B.Sc. in Electronics and Communications Engineering Benha Univ., Egypt
Project Title: A Motorized Wheelchair for Handicapped.
• Ibrahim A. Seleem, H. El-Hussieny, Samy F. M. Assal and Hiroyuki Ishii, “Development and Stability Analysis of an Imitation Learning-based Pose Planning Approach for Multi-section Continuum Robot.", IEEE Access (2020).
• Ibrahim A. Seleem, Samy F. M. Assal, Hiroyuki Ishii and H. El-Hussieny, “Demonstration-Guided Pose Planning and Tracking for Multi-section Continuum Robots Considering Robot Dynamics.", IEEE Access (2019).
• Margaret M. Coad, Laura H. Blumenschein, Sadie Cutler, Javier A. R. Zepeda, Nicholas D. Naclerio
• H. El-Hussieny, Usman Mehmood, Jee-Hwan Ryu, Elliot W. Hawkes, and Allison M. Okamura. “Vine Robots: Design, Teleoperation, and Deployment for Navigation and Exploration.", IEEE Robotics & Automation Magazine (2019).
• H. El-Hussieny and Jee-Hwan Ryu, “Inverse Discounted-based LQR Algorithm for Learning Human Movement Behaviors.”, Applied Intelligence, 2018, 49 (4), pp.1489-1501.
• H. El-Hussieny, Samy F. M. Assal and Jee-Hwan Ryu, “SoTCM: a scene-oriented task complexity metric for gaze-supported teleoperation tasks.” Intelligent Service Robotics, 11, 2018, pp.279-288.
• H. El-Hussieny, A.A. Abouelsoud, Samy F. M. Assal and Said M. Megahed, “Adaptive learning of human motor behaviors: An evolving inverse optimal control approach.” Engineering Applications of Artificial Intelligence, 50, 2016, pp.115-124.
• H. El-Hussieny, Samy F. M. Assal, and M. Abdellatif, “Robotic Exploration- New Heuristic Backtracking Algorithm, Performance Evaluation and Complexity Metric”, International Journal of Advanced Robotic Systems, 12, 2015, pp.33.
• M. E. Shalabi, H. El-Hussieny, A. A. Abouelsoud, and Ahmed M. R. Fath Elbab, “ Control of Automotive Air-Spring Suspension System Using Z-Number Based Fuzzy System", in the International Conference on Robotics and Biomimetics, Automation and Robotics (ROBIO 2019), pp. 1306-1311, IEEE, 2019.
• Oladayo Solomon and H. El-Hussieny, “An ANFIS-based Human Activity Recognition using IMU sensor Fusion," in Proc. of IEEE Novel Intelligent and Leading Emerging Sciences Conference (NILE2019), Egypt, Vol. 1, pp. 34-37, IEEE, 2019.
• Oladayo Solomon, Samy F. M. Assal and H. El-Hussieny, "Towards Development of an Autonomous Robotic System for Beard Shaving Assistance for Disabled People," in Proc. of IEEE International Conference on Systems, Man, and Cybernetics (SMC), Bari, Italy, pp. 3435-3440. IEEE, 2019.
• H. El-Hussieny, Sang-Goo Jeong and Jee-Hwan Ryu, “Dynamic Modeling of A Class of Soft Growing Robots Using Euler-Lagrange Formalism" In 2019 SICE Annual Conference, Japan, pp. 453-458, IEEE (2019).
• M. E. Shalabi, H. El-Hussieny, A. A. Abouelsoud, and Ahmed M. R. Fath Elbab, “Finite Control Augmented with Fuzzy Logic for Automotive Air-Spring Suspension System", in The 16th. International Conference of Informatics in Control, Automation and Robotics (ICINCO 2019) [Accepted].
• Mohamed G. B. Atia, Omar Salah, and H. El-Hussieny, “OGPR: An Obstacle-Guided Path Refinement Approach for Mobile Robot Path Planning." in Proc. of the 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2018, pp. 844-849
• H. El-Hussieny, U. Mehmood, Z. Mehdi, S-G. Jeong, M. Usman, E. W. Hawkes, A. M. Okamura, and J.-H. Ryu, “Development and evaluation of an intuitive flexible interface for teleoperating soft growing robots," in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, pp. 4995-5002.
• Ibrahim A. Seleem, H. El-Hussieny and Samy F. M. Assal, “Motion Planning for Continuum Robots: A Learning from Demonstration Approach," 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), Nanjing, China, 2018, pp. 868-873.
• Ibrahim A. Seleem, H. El-Hussieny and Samy F. M. Assal, "Development of a Demonstration-Guided Motion Planning for Multi-section Continuum Robots," in Proc. of IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan, 2018, pp. 333-338.
• H. El-Hussieny, A. Asker and O. Salah, “Learning the sit-to-stand human behavior: An inverse optimal control approach," 2017 13th. International Computer Engineering Conference (ICENCO), Cairo, Egypt, 2017, pp. 112-117.
- Soft robotics applications in health and social care.
- Human-Robot Interaction.
- Learning by Demonstrations.