The Marie Curie Initial Training Network, SMART-E (Sustainable Manufacturing through Advanced Robotics Training in Europe), coordinated by the University of Salford, has launched a new European research and training programme on Advanced Robotics under the European Union programme FP7-PEOPLE-2013-ITN with a total budget of approximately €4 million. SMART-E will develop a leading European Doctoral Training programme, training 15 high calibre Researchers in the areas of Dexterous, Soft and Compliant Robotics in Manufacturing; Reconfigurable and Logistics Robotics; and Safety & Human Robot Interaction.
Coordinated by Prof Samia Nefti-Meziani, SMART-E brings together a team of world-renowned experts in robotics from leading universities in the UK, Germany, Italy and Switzerland ((University of Salford, University of Sheffield, Technical University of Munich, Scuola Superiore Sant'Anna, Italian Institute of Technology,University of Zurich) and a world leading manufacturers and end users of Automation in the Aerospace and Food sectors including FESTO, AIRBUS and the Advanced Manufacturing Research Centre (AMRC). The team is supported by a number of additional leading Universities, research laboratories and industries as associated partners.
The Autonomous Systems & Robotics Research Centre holds the leading role in Autonomous mission planning and management, task allocation, hybrid optimisation, and intelligent decision making in the GAMMA Programme (Growing Autonomous Mission Management Applications).
Lead Partners in this programme include North West Aerospace Alliance (NWAA) and BAE Systems, together with the Universities of Salford, Manchester, Lancaster, Liverpool, UCLAN, Liverpool (including the Virtual Engineering Centre), and National Nuclear Laboratories.
GAMMA is a three year £9.1 million Autonomous Systems programme aimed at driving SME engagement and developing technology within the emerging autonomous systems markets. GAMMA technology areas of interest include data management, image processing, sensing and communication and mission planning and management.
Development of a novel Soft, variable stiffness continuum manipulator.
The future of manufacturing will likely require robots working close to, and in collaboration with humans. This has led to the development of ‘soft’ and compliant robotic systems which mimic the soft interaction between people. This study is developing a physically soft manipulator able to vary its stiffness depending upon its task requirements. This will enable it to operate in a safe low stiffness mode when moving large distances but switch to a high stiffness mode to allow for precise/accurate position control. This will result in a robot manipulator which unlike most ‘soft’ systems is able to achieve high levels of accuracy.
One of the main challenges of robotic grasping is preventing slippage while manipulating objects. Slippage can cause the grasped object to fall and break, which might lead to a grievous situation especially if the handled object is expensive or contains hazardous substances. Also, grasping an object with sufficient force to prevent slippage, whilst not damaging or deforming the shape of the object proves to be an intricate challenge despite the existence of a huge body of literature on robotic grasping. Saber’s research focuses at designing a nonlinear impedance-slip control for robotic hands, grippers and end effectors. When grasping objects, the controller should robustly overcome external nonlinear disturbances, along with inaccuracies in the system model, preventing slippage and minimizing deformation of objects.
Current sensing technologies are very challenging to implement over 3D surfaces, sometimes expensive and difficult to replace, while a soft and low-cost solution able to reproduce some of the properties of our skin is needed, especially on high-deformable areas as the robotic-joints. In this way it is possible to enable and maximise the quality of the robot interactions’ with the surrounding environment.
This work describes an initial step towards the realisation of a stretchable and deformation-responsive “sensitive skin” for reproducing the human sensing capabilities in robotic applications. We are developing a sensor as a pressure sensitive fabric material which responds to external stimuli by changing its electrical conductivity. The stretchable sensor is surrounded by electrodes for the electrical circuit and in this way, since it does not present internal wires, it is extremely soft and stretchable. When an external stimulus is applied, the variations in the internal conductivity of the sensitive skin will change the distribution of the injected electrical current inside it, resulting in a variation of the measured voltages at the boundary. The collected potentials are then sent to a software for reconstructing the image of the internal conductivity distribution.
So far a second prototype of the experimental set-up with PCB has been developed. We have been working on the voltage data and study the performance parameters for the optimisation of the drive patterns. We have demonstrated that, depending on the present stimuli position over the conductive domain, the selection of electrodes on which current injection and voltage reading are performed, can be chosen dynamically resulting in an improved quality of the reconstructed image and system performance. At the moment we are focusing on developing reconstruction algorithms to improve the time and spatial resolution of the sensor and to achieve touch interpretation.
My current research is on developing a novel self-healing framework for Robots and Complex machinery. The key behind this framework is the mathematical modelling of the degrading components within a mechanical system, where the wear interactions between components are taken into account, leading to a more accurate indication of system health, and thus maintenance actions can be scheduled accordingly minimising human intervention, increasing the autonomous aspect of the system and giving the appearance of self-healing. The self-healing framework will start from the diagnostics and prognostics of a system; it uses a data-driven approach, using statistical modelling and machine learning. It works by classifying normal response of a system under a specific operation scheme, which then makes it easier to identify incipient faults; this will also lead to more accurate remaining useful lifetime calculations, and so prevent downtime that leads to economic losses and in some cases human casualties.
Recently, UAVs are promising to be a cost-effective and safe approach to improve awareness in any given environment. Although UAV technologies are reliable in gathering and sharing information with base stations, current technologies are limited to short flights. Hence available multicopters are not permissive. Murad is currently working on a self-regulated, fail safe hybrid propulsion system which will improve the flight endurance increasing the effectiveness in battle scenarios.
Designing a multi-robot system provides numerous advantages for many applications, such as low cost, multi-tasking and more efficient group work. While the rigidity of the robots used in industrial and medical application increase the probability of risk of injury. Therefore, many researches are done to increase the safety factor for robot-human interaction, as a result, either the separated between the human and robot is suggested or the force shutdown to robot system is applied. These solutions might be useful for industrial application but it is not for medical and the application require the direct interaction between the human the machine. To overcome the rigidity problem, a soft robot arm is presented. Ala aims to design and build multi soft robot system and design a suitable cooperative control system.
Mohd Nadhir Ab Wahab
Swarm Intelligence (SI) is one of the prominent techniques employed to solve optimisation problems. It has been applied to problems pertaining to engineering, schedule, planning, networking and design. However, this technique has two main limitations. First, the SI technique may not be suitable for real-time application, as it does not have the same aspects of limitations as a real-time platform. Second, setting the parameter for SI techniques to produce the most promising outcome is challenging. Therefore, this study has been conducted to overcome these two limitations. Based on the literature, Particle Swarm Optimization (PSO) was selected as the main SI for this study, due to its proven performances, abilities and simplicity. Five new techniques were created based on the PSO technique in order to address the two limitations. The first two techniques focused on the first limitation, while the other three techniques focused on the latter. Three main experiments (benchmark problems, engineering problems, path planning problems) were designed to assess the capabilities and performances of these five new techniques. These new techniques were also compared against several other well-established SI techniques such as the Genetic Algorithm (GA), Differential Equation (DE) and Cuckoo Search Algorithm (CSA). Potential Field (PF), Probabilistic Road Map (PRM), Rapidly-explore Random Tree (RRT) and Dijkstra’s Algorithm (DA) were also included in the path planning problem in order to compare these new techniques’ performances against Classical methods of path planning. Results showed all five introduced techniques managed to outperform or at least perform as good as well-established techniques in all three experiments.
Wajid Rasheed Ismaeel Al-Rikabi
Fuzzy type-2 controllers can easily deal with systems nonlinearity and utilise human expertise to solve many complex control problems; they are also very good at processing uncertainty, which exists in many robotic systems, such as autonomous vehicles. However, their computational cost is high, especially at the type reduction stage. In this research, we aimed to reduce the computation cost of the type reduction stage, thus to facilitate faster performance speed and increase the number of actions able to be operated in one microprocessor. Proposed here are adaptive integration principles with a binary successive search technique to locate any straight sections in fuzzy sets, then using them to cut the cost of the weighted average computation, which runs in many type reductions. A variable adaptation rate is suggested during the type reduction iterations to reduce the computation cost further. The influence of the proposed approaches on the fuzzy type-2 controller’s error has been mathematically analysed and then experimentally measured using a wall following behaviour, which is the most important action for many autonomous vehicles. Results show a performance time-gain exceeding 200%.
This study develops a new accelerated version of the enhanced Karnik-Mendel type reducer by using better initialisations and better indexing scheme. The resulting performance time-gain reached 170%, with respect to the original version. A further cut in the type reduction time was achieved by proposing a One-Go type reduction procedure. This technique can reduce multiple sets altogether in one pass, thus eliminating much of the redundant calculations needed to carry out the reduction individually. All the proposed type reduction enhancements were evaluated in terms of their execution time-gain and performance error using every possible fuzzy firing level combination. Tests were then performed using a real autonomous vehicle navigating in a relatively complex arena field with acute, right, obtuse, and reflex angled corners, to assure a wide variety of operation conditions. A simplified state hold technique using Schmitt-trigger principles and dynamic sense pattern control was suggested and implemented to assure small rule base size and to obtain a more accurate evaluation of the type reduction stages.
This study focuses directly on analysis and evaluation of human gait features such as spatial gait data, temporal gait data, spatiotemporal gait data, and kinematic gait data. The changes in gait features can be used for assisting in clinical diagnoses especially in cognitive diseases such as; multiple sclerosis. In this study, Microsoft Kinect v2 has been chosen to collect data form participants who are instructed to walk about 3 meters in the front of the camera which can provide data as 3D skeletal numerical data for 25 joints.
Loai Al Abeach
This research presents the design of a variable stiffness, soft, three fingered dexterous gripper. The gripper uses two designs of McKibben muscles. Extensor muscles which increase in length when pressurised are used to form the fingers of the gripper. Contractor muscles which decrease in length when pressurised are then used to apply forces to the fingers via tendons which cause flexion and extension of the fingers. The two types of muscles are arranged to act antagonistically and this means that by raising the pressure in all of the pneumatic muscles the stiffness of the system can be increased without a resulting change in finger position. The research presents the design of the gripper, some basic kinematics to describe its function and then experimental results demonstrating the ability to adjust the bending stiffness of the gripper’s fingers. It has been demonstrated that the finger’s bending stiffness can be increased by over 150%. The research concludes by demonstrating that the fingers can be closed loop position controlled and are able to track step and sinusoidal inputs.
In addition, three more end effectors are developed in this research as well. Two of them are modified variable stiffness, pneumatic, soft robot gripper designed to enhance the performance of the previous one. The third once which is variable stiffness too, however, its constructed using granular jamming criteria and its work depends on the negative pressure in contrast with the previous three soft grippers.
Soft wearable robots are efficient alternatives to rigid-frame exoskeletons because they are compact and lightweight. We are manufactured a wearable robot for human upper-limp power assist and rehabilitation because a physically handicapped elderly and disabled people can expect to live more independent life by using this kind of devices. We are developing a suitable intelligent control to control this device efficiently.
The Center collectively attracted over 30 research grants including: