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Industrial robots are delivering more and more manipulation services in manufacturing. However, when the task is complex, it is difficult to programme a robot to fulfil all the requirements because even a relatively simple task such as a peg-in-hole insertion contains many uncertainties, e.g. clearance, initial grasping position and insertion path. Humans, on the other hand, can deal with these variations using their vision and haptic feedback. Although humans can adapt to uncertainties easily, most of the time, the skilled based performances that relate to their tacit knowledge cannot be easily articulated. Even though the automation solution may not fully imitate human motion since some of them are not necessary, it would be useful if the skill based performance from a human could be firstly interpreted and modelled, which will then allow it to be transferred to the robot. This thesis aims to reduce robot programming efforts significantly by developing a methodology to capture, model and transfer the manual manufacturing skills from a human demonstrator to the robot. Recently, Learning from Demonstration (LfD) is gaining interest as a framework to transfer skills from human teacher to robot using probability encoding approaches to model observations and state transition uncertainties. In close or actual contact manipulation tasks, it is difficult to reliabley record the state-action examples without interfering with the human senses and activities. Therefore, wearable sensors are investigated as a promising device to record the state-action examples without restricting the human experts during the skilled execution of their tasks. Firstly to track human motions accurately and reliably in a defined 3-dimensional workspace, a hybrid system of Vicon and IMUs is proposed to compensate for the known limitations of the individual system. The data fusion method was able to overcome occlusion and frame flipping problems in the two camera Vicon setup and the drifting problem associated with the IMUs. The results indicated that occlusion and frame flipping problems associated with Vicon can be mitigated by using the IMU measurements. Furthermore, the proposed method improves the Mean Square Error (MSE) tracking accuracy range from 0.8˚ to 6.4˚ compared with the IMU only method. Secondly, to record haptic feedback from a teacher without physically obstructing their interactions with the workpiece, wearable surface electromyography (sEMG) armbands were used as an indirect method to indicate contact feedback during manual manipulations. A muscle-force model using a Time Delayed Neural Network (TDNN) was built to map the sEMG signals to the known contact force. The results indicated that the model was capable of estimating the force from the sEMG armbands in the applications of interest, namely in peg-in-hole and beater winding tasks, with MSE of 2.75N and 0.18N respectively. Finally, given the force estimation and the motion trajectories, a Hidden Markov Model (HMM) based approach was utilised as a state recognition method to encode and generalise the spatial and temporal information of the skilled executions. This method would allow a more representative control policy to be derived. A modified Gaussian Mixture Regression (GMR) method was then applied to enable motions reproduction by using the learned state-action policy. To simplify the validation procedure, instead of using the robot, additional demonstrations from the teacher were used to verify the reproduction performance of the policy, by assuming human teacher and robot learner are physical identical systems. The results confirmed the generalisation capability of the HMM model across a number of demonstrations from different subjects; and the reproduced motions from GMR were acceptable in these additional tests. The proposed methodology provides a framework for producing a state-action model from skilled demonstrations that can be translated into robot kinematics and joint states for the robot to execute. The implication to industry is reduced efforts and time in programming the robots for applications where human skilled performances are required to cope robustly with various uncertainties during tasks execution.

This dissertation is relevant to structural engineers focusing on seismic design of structures using reinforced masonry. Specifically the thesis focuses on the seismic performance of reinforced masonry shear walls as seismic force resisting systems. / Reinforced masonry (RM) has been gaining a wide acceptance in the low- and mid-rise construction market as an economic and durable structural system. However, challenges still exist in the area of seismic design because of the poor performance of unreinforced masonry during recent earthquake events in Iran 2003, Haiti 2010, Japan 2011, New Zealand 2011 and Nepal 2015. The dissertation investigated the seismic performance of six concrete block structural walls in an effort to evaluate their force-, displacement- and performance- based seismic design parameters. The walls fall under the ductile shear wall/special reinforced wall seismic force resisting system (SFRS) classification according to the current North American masonry design standards. More specifically, the dissertation is focused on evaluating if such walls, designed under the same prescriptive design provisions, having different cross-section configurations would possess similar seismic performance parameters. This was established through an experimental and analytical program by subjecting the walls to a displacement controlled quasi-static cyclic analysis. Different wall configurations were tested including, rectangular, flanged and slab-coupled walls. Test results confirmed that walls designed under the same SFRS classification, but with different configurations, have different seismic performance parameters that included ductility capacity; yield and post yield displacement; stiffness degradation; period elongation and equivalent viscous damping. The current North American masonry design provisions do not account for such difference in the ductility capacities between the walls. The thesis analyses were concluded by quantifying the seismic vulnerability of a RM SFRS comprised of shear walls similar to those tested, through the development of collapse fragility curves and the assignment of an adjusted collapse margin ratio, ACMR following the FEMA P-58 and P-695 guidelines. The system were deemed acceptable since the ACMR was greater than ACMR10% (2.35 > 2.31). Therefore, the selected RM SFRS which was designed to meet the prescriptive requirements of the ductile masonry walls classification of the CSA S304 (CSA 2014), shows potential capacity against collapse under high intensity earthquakes in one of the highest seismic zones in western Canada and it should be considered as a viable SFRS to be used in seismic design. The procedure described in the chapter can be adopted to investigate the collapse fragility of other SFRS in different seismic regions through careful selection and scaling of the ground motion records associated with such region's seismicity. / Dissertation / Doctor of Philosophy (PhD)

The controlled rocking heavy timber wall (CRHTW) is a high-performance structural solution that was first developed in New Zealand, mainly considering Laminated Veneer Lumber (LVL), to resist high seismic loads without sustaining structural damage. The wall responds in bending and shear to small lateral loads, and it rocks on its foundation in response to large seismic loads. In previous studies, rocking has been controlled by both energy dissipation elements and post-tensioning, and the latter returns the wall to its original position after a seismic event. The controlled rocking response avoids the need for structural repair after an earthquake, allowing for more rapid return to occupancy than in conventional structures. Whereas controlled rocking walls with supplemental energy dissipation have been studied before using LVL, this thesis proposes an adapted CRHTW in which the design and construction cost and complexity are reduced for low-to-moderate seismic hazard regions by removing supplemental energy dissipation and using cross-laminated timber (CLT) because of its positive economic and environmental potential in the North American market. Moreover, whereas previous research has focussed on direct displacement-based design procedures for CRHTWs, with limited consideration of force-based design parameters, this thesis focusses on force-based design procedures that are more common in practice. A design and analysis process is outlined for the adapted CRHTW, based on a similar methodology for controlled rocking steel braced frames. The design process includes a new proposal to minimize the design forces while still controlling peak drifts, and it also includes a new proposal for predicting the influence of the higher modes by referring to previous research on the capacity design of controlled rocking steel braced frames. Also, a numerical model is outlined, including both a baseline version and a lower-bound model based on comparison to experimental data. The numerical model is used for non-linear time-history analysis of a prototype design, confirming the expected performance of the adapted CRHTW, and the model is also used for incremental dynamic analyses of three-, six-, and nine-storey prototypes, which show a low probability of collapse. / Thesis / Master of Applied Science (MASc) / The controlled rocking heavy timber wall (CRHTW) is a high-performance structural solution that was developed to resist high seismic loads without sustaining structural damage. The wall responds in bending and shear to small lateral loads, and it rocks on its foundation in response to large seismic loads. In previous studies, rocking has been controlled by both energy dissipation elements and post-tensioning; the latter returns the wall to its original position after a seismic event. This controlled rocking behaviour mitigates structural damage and costly repairs. This thesis explores the value of an adapted CRHTW in which the design and construction costs and complexity are reduced for low-to-moderate seismic hazard regions by using post-tensioning but no supplemental energy dissipation. A design and analysis process is outlined; numerical analysis confirms the expected performance of the adapted CRHTW; and the system is shown to have a low probability of collapse.

The scale of engineering problems has sharply increased over the last twenty years. Larger coupled systems, increasing complexity, and limited resources create a need for methods that automatically decompose problems into manageable sub-problems by discovering and leveraging problem structure. The ability to learn the coupling (inter-dependence) structure and reorganize the original problem could lead to large reductions in the time to analyze complex problems. Such decomposition methods could also provide engineering insight on the fundamental physics driving problem solution. This work forwards the current state of the art in engineering decomposition through the application of techniques originally developed within computer science and information theory. The work describes the current state of automatic problem decomposition in engineering and utilizes several promising ideas to advance the state of the practice. Mutual information is a novel metric for data dependence and works on both continuous and discrete data. Mutual information can measure both the linear and non-linear dependence between variables without the limitations of linear dependence measured through covariance. Mutual information is also able to handle data that does not have derivative information, unlike other metrics that require it. The value of mutual information to engineering design work is demonstrated on a planetary entry problem. This study utilizes a novel tool developed in this work for planetary entry system synthesis. A graphical method, force-based clustering, is used to discover related sub-graph structure as a function of problem structure and links ranked by their mutual information. This method does not require the stochastic use of neural networks and could be used with any link ranking method currently utilized in the field. Application of this method is demonstrated on a large, coupled low-thrust trajectory problem. Mutual information also serves as the basis for an alternative global optimizer, called MIMIC, which is unrelated to Genetic Algorithms. Advancement to the current practice demonstrates the use of MIMIC as a global method that explicitly models problem structure with mutual information, providing an alternate method for globally searching multi-modal domains. By leveraging discovered problem inter-dependencies, MIMIC may be appropriate for highly coupled problems or those with large function evaluation cost. This work introduces a useful addition to the MIMIC algorithm that enables its use on continuous input variables. By leveraging automatic decision tree generation methods from Machine Learning and a set of randomly generated test problems, decision trees for which method to apply are also created, quantifying decomposition performance over a large region of the design space.

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This Master Thesis deals with the drawing algorithms of graphs known from the mathematical theory. These algorithms deals with an appropriate distribution of the graph vertices in order to obtain the most clear and readable graphs for human readers. The main objective of this work was also to implement the drawing algorithm in the application that would allow to edit the graph. This work deals also with graphs representation in computers.