TESTING FLEXIBLE GRIPPERS FOR GEOMETRIC AND SURFACE GRASPING CONFORMITY IN RECONFIGURABLE ASSEMBLY SYSTEMS

The ongoing development in manufacturing technology facilitates flexibility in production and faces challenges of product handling. Flexibility was required in the form of adaptable grippers for robotic arms in pick-and-place procedures for reconfigurable assembly systems. A conceptual system was designed and tested according to the surface geometric conformity of grasped objects. The system proposed was a biologically inspired Fin Ray Effect® gripper. Grasping occurs due to the deformation of the rib structure of the appendage. The appendages were simulated for conformity by means of a finite element analysis, and performance was analysed by means of a physical sample mass test and a force test

EFFICIENCY OF FLEXIBLE FIXTURES: DESIGN AND CONTROL

The manufacturing industries have been using flexible production technologies to meet the demand for customisation. As a part of production, fixtures have remained limited to dedicated technologies, even though numerous flexible fixtures have been studied and proposed by both academia and industry. The integration of flexible fixtures has shown that such efforts did not yield the anticipated performance and resulted in inefficiencies of cost and time. The fundamental formulation of this thesis addresses this issue and aims to increase the efficiency of flexible fixtures.To realise this aim, the research in this thesis poses three research questions. The first research question investigates the efficiency description of flexible fixtures in terms of the criteria. Relative to this, the second research question investigates the use of efficiency metrics to integrate efficiency criteria into a design procedure. Once the efficiency and design aspects have been established, the third research question investigates the active control of flexible fixtures to increase their efficiency. The results of this thesis derive from the outcome of seven studies investigating the automotive and aerospace industries. The results that answer the first research question use five criteria to establish the efficiency of flexible fixtures. These are: fundamental, flexibility, cost, time and quality. By incorporating design characteristics in respect of production system paradigms, each criterion is elaborated upon using relevant sub-criteria and metrics. Moreover, a comparative design procedure is presented for the second research question and comprising four stages (including mechanical, control and software aspects). Initially, the design procedure proposes conceptual design and verification stages to determine the most promising flexible fixture for a target production system. By executing detailed design and verification, the design procedure enables a fixture designer to finalise the flexible fixture and determine its efficiency. Furthermore, a novel parallel kinematics machine is presented to demonstrate the applicability of the design procedure’s analytical steps and illustrate how appropriate kinematic structures can facilitate the efficiency-orientated design of flexible fixtures.Based on the correlation established by the controller software’s design procedure, the active control of flexible fixtures directly affects the quality criterion of flexible fixture efficiency. This provides the answer to the third research question, on general control strategies for active control of flexible fixtures. The introduction of a system model and manipulator dynamics proposes force and position control strategies. It is shown that any flexible fixture using a kinematic class can be controlled, to regulate the force and position of a workpiece and ensure that process nominals are preserved. Moreover, using both direct and indirect force control strategies, a flexible fixture’s role in active control can be expanded into a system of actively controlled fixtures that are useful in various processes. Finally, a position controller is presented which has the capacity to regulate both periodic and non-periodic signals. This controller uses an additional feedforward scheme (based on the Hilbert transform) in parallel with a feedback mechanism. Thus, the position controller enables flexible fixtures to regulate the position of a workpiece in respect of any kind of disturbance

Part clamping and fixture geometric adaptability for reconfigurable assembly systems.

Masters of Science in Mechanical Engineering. University of KwaZulu-Natal. Durban, 2017.The Fourth Industrial Revolution is leading towards cyber-physical systems which justified research efforts in pursuing efficient production systems incorporating flexible grippers. Due to the complexity of assembly processes, reconfigurable assembly systems have received considerable attention in recent years. The demand for the intricate task and complicated operations, demands the need for efficient robotic manipulators that are required to manoeuvre and grasp objects effectively. Investigations were performed to understand the requirements of efficient gripping systems and existing gripping methods. A biologically inspired robotic gripper was investigated to establish conformity properties for the performance of a robotic gripper system. The Fin Ray Effect® was selected as a possible approach to improve effective gripping and reduce slippage of component handling with regards to pick and place procedures of assembly processes. As a result, the study established the optimization of self-adjusting end-effectors. The gripper system design was simulated and empirically tested. The impact of gripping surface compliance and geometric conformity was investigated. The gripper system design focused on the response of load applied to the conformity mechanism called the Fin Ray Effect®. The appendages were simulated to determine the deflection properties and stress distribution through a finite element analysis. The simulation proved that the configuration of rib structures of the appendages affected the conformity to an applied force representing an object in contact. The system was tested in real time operation and required a control system to produce an active performance of the system. A mass loading test was performed on the gripper system. The repeatability and mass handling range was determined. A dynamic operation was tested on the gripper to determine force versus time properties throughout the grasping movement for a pick and place procedure. The fluctuating forces generated through experimentation was related to the Lagrangian model describing forces experienced by a moving object. The research promoted scientific contribution to the investigation, analysis, and design of intelligent gripping systems that can potentially be implemented in the operational processes of on-demand production lines for reconfigurable assembly systems

Reconfigurable End Effector Allowing For In-Hand Manipulation Without Finger Gaiting Or Regrasping

The goal of this thesis is to move a step towards the solution of the bin picking problem. A novel metamorphic end effector is proposed, tested for proof of concept and analyzed using standard techniques of degrees of freedom and graph theory as well as a classical dynamic analysis. Once proof of concept was achieved, the results from the analysis were formed into an optimization program with the hope of finding a more stable, predictable mechanism

Automated freeform assembly of threaded fasteners

Over the past two decades, a major part of the manufacturing and assembly market has been driven by its customer requirements. Increasing customer demand for personalised products create the demand for smaller batch sizes, shorter production times, lower costs, and the flexibility to produce families of products - or different parts - with the same sets of equipment. Consequently, manufacturing companies have deployed various automation systems and production strategies to improve their resource efficiency and move towards right-first-time production. However, many of these automated systems, which are involved with robot-based, repeatable assembly automation, require component- specific fixtures for accurate positioning and extensive robot programming, to achieve flexibility in their production. Threaded fastening operations are widely used in assembly. In high-volume production, the fastening processes are commonly automated using jigs, fixtures, and semi-automated tools. This form of automation delivers reliable assembly results at the expense of flexibility and requires component variability to be adequately controlled. On the other hand, in low- volume, high- value manufacturing, fastening processes are typically carried out manually by skilled workers. This research is aimed at addressing the aforementioned issues by developing a freeform automated threaded fastener assembly system that uses 3D visual guidance. The proof-of-concept system developed focuses on picking up fasteners from clutter, identifying a hole feature in an imprecisely positioned target component and carry out torque-controlled fastening. This approach has achieved flexibility and adaptability without the use of dedicated fixtures and robot programming. This research also investigates and evaluates different 3D imaging technology to identify the suitable technology required for fastener assembly in a non-structured industrial environment. The proposed solution utilises the commercially available technologies to enhance the precision and speed of identification of components for assembly processes, thereby improving and validating the possibility of reliably implementing this solution for industrial applications. As a part of this research, a number of novel algorithms are developed to robustly identify assembly components located in a random environment by enhancing the existing methods and technologies within the domain of the fastening processes. A bolt identification algorithm was developed to identify bolts located in a random clutter by enhancing the existing surface-based matching algorithm. A novel hole feature identification algorithm was developed to detect threaded holes and identify its size and location in 3D. The developed bolt and feature identification algorithms are robust and has sub-millimetre accuracy required to perform successful fastener assembly in industrial conditions. In addition, the processing time required for these identification algorithms - to identify and localise bolts and hole features - is less than a second, thereby increasing the speed of fastener assembly

Real-Time Hybrid Visual Servoing of a Redundant Manipulator via Deep Reinforcement Learning

Fixtureless assembly may be necessary in some manufacturing tasks and environ-ments due to various constraints but poses challenges for automation due to non-deterministic characteristics not favoured by traditional approaches to industrial au-tomation. Visual servoing methods of robotic control could be effective for sensitive manipulation tasks where the desired end-effector pose can be ascertained via visual cues. Visual data is complex and computationally expensive to process but deep reinforcement learning has shown promise for robotic control in vision-based manipu-lation tasks. However, these methods are rarely used in industry due to the resources and expertise required to develop application-specific systems and prohibitive train-ing costs. Training reinforcement learning models in simulated environments offers a number of benefits for the development of robust robotic control algorithms by reducing training time and costs, and providing repeatable benchmarks for which algorithms can be tested, developed and eventually deployed on real robotic control environments. In this work, we present a new simulated reinforcement learning envi-ronment for developing accurate robotic manipulation control systems in fixtureless environments. Our environment incorporates a contemporary collaborative industrial robot, the KUKA LBR iiwa, with the goal of positioning its end effector in a generic fixtureless environment based on a visual cue. Observational inputs are comprised of the robotic joint positions and velocities, as well as two cameras, whose positioning reflect hybrid visual servoing with one camera attached to the robotic end-effector, and another observing the workspace respectively. We propose a state-of-the-art deep reinforcement learning approach to solving the task environment and make prelimi-nary assessments of the efficacy of this approach to hybrid visual servoing methods for the defined problem environment. We also conduct a series of experiments ex-ploring the hyperparameter space in the proposed reinforcement learning method. Although we could not prove the efficacy of a deep reinforcement approach to solving the task environment with our initial results, we remain confident that such an ap-proach could be feasible to solving this industrial manufacturing challenge and that our contributions in this work in terms of the novel software provide a good basis for the exploration of reinforcement learning approaches to hybrid visual servoing in accurate manufacturing contexts

Fixtureless automated incremental sheet metal forming

Die-based forming is a technology used by many industries to form metal panels. However, this method of forming lacks flexibility and cost effectiveness. In such cases, manual panel beating is typically undertaken for incremental forming of metal panels. Manual panel forming is a highly skilled operation with very little documentation and is disappearing due to non-observance and a lack of interest. Confederation of British Metal forming (CBM) and Institution of Sheet Metal Engineering (ISME) have realised the need for capturing and understanding manual skills used by panel beaters to preserve the knowledge. At the same time, industries seek for alternative panel forming solutions to produce high quality and cost-effective parts at low volume and reduce the repetitive, yet adaptive parts of the panel forming process to free up skilled workers to concentrate on the forming activities that are more difficult to automate. Incremental forming technologies, currently in practice, lack adaptability as they require substantial fixtures and dedicated tools. In this research a new proof-of-concept fixtureless automated sheet metal forming approach was developed on the basis of human skills captured from panel beaters. The proposed novel approach, named Mechatroforming®, consists of integrated mechanisms to form simple sheet metal parts by manipulating the workpiece using a robotic arm under a repetitive hammering tool. Predictive motion planning based on FEA was analysed and the manual forming skills were captured using a motion capture system. This facilitated the coordinated hammering and motion of the part to produce the intended shape accurately. A 3D measurement system with a vertical resolution of 50μm was also deployed to monitor the formation of the parts and make corrections to the forming path if needed. Therefore, the developed mechatronic system is highly adjustable by robotic motion and was closed loop via the 3D measurement system. The developed automated system has been tested rigorously, initially for bowl shape parts to prove the principle. The developed system which is 98% repeatable for depth and diameter, is able to produce targeted bowl shape parts with ±1% dimensional accuracy, high surface quality, and uniform material thickness of 0.95mm when tested with aluminium. It is envisaged that by further research, the proposed approach can be extended to form irregular and more complicated shapes that are highly in demand in various industries

Adaptive and reconfigurable robotic gripper hands with a meso-scale gripping range

Grippers and robotic hands are essential and important end-effectors of robotic manipulators. Developing a gripper hand that can grasp a large variety of objects precisely and stably is still an aspiration even though research in this area has been carried out for several decades. This thesis provides a development approach and a series of gripper hands which can bridge the gap between micro-gripper and macro-gripper by extending the gripping range to the mesoscopic scale (meso-scale). Reconfigurable topology and variable mobility of the design offer versatility and adaptability for the changing environment and demands. By investigating human grasping behaviours and the unique structures of human hand, a CFB-based finger joint for anthropomorphic finger is developed to mimic a human finger with a large grasping range. The centrodes of CFB mechanism are explored and a contact-aided CFB mechanism is developed to increase stiffness of finger joints. An integrated gripper structure comprising cross four-bar (CFB) and remote-centre-of-motion (RCM) mechanisms is developed to mimic key functionalities of human hand. Kinematics and kinetostatic analyses of the CFB mechanism for multimode gripping are conducted to achieve passive-adjusting motion. A novel RCM-based finger with angular, parallel and underactuated motion is invented. Kinematics and stable gripping analyses of the RCM-based multi-motion finger are also investigated. The integrated design with CFB and RCM mechanisms provides a novel concept of a multi-mode gripper that aims to tackle the challenge of changing over for various sizes of objects gripping in mesoscopic scale range. Based on the novel designed mechanisms and design philosophy, a class of gripper hands in terms of adaptive meso-grippers, power-precision grippers and reconfigurable hands are developed. The novel features of the gripper hands are one degree of freedom (DoF), self-adaptive, reconfigurable and multi-mode. Prototypes are manufactured by 3D printing and the grasping abilities are tested to verify the design approach.EPSR