Design of an Under-Actuated Exoskeleton System for Walking Assist While Load Carrying

This study proposes an under-actuated wearable exoskeleton system to carry a heavy load. To synchronize that system with a user, a feasible modular-type wearable system and its corresponding sensor systems are proposed. The design process of the modular-type exoskeleton for lower extremities is presented based on the considered requirements. To operate the system with the user, human walking analysis and intention signal acquisition methods for actuating the proposed system are developed. In particular, a sensing data estimation strategy is applied to synchronize the exoskeleton system with a user correctly. Finally, several experiments were performed to evaluate the performance of the proposed exoskeleton system by measuring the electromyography signal of the wearer's muscles while walking on level ground and climbing up stairs with 20- to 40-kg loads, respectively.     

Local rolling and tilting capability analysis of fully parallel linear actuated platform-type manipulators

Two problems associated with the local rotatability of two types of fully parallel linearly actuated platform manipulators are investigated in this paper. The first problem is to find the physically allowable region that the movable platform can be freely rolled about any given direction at any specified position. The second problem is to evaluate the maximum angle that the movable platform can be tilted about any given position and orientation. The kinematic constraints involved in these problems are the stroke limitation of the linear actuators, the motion constraints of the passive spherical and universal joints, and the interference condition between the supporting limbs. A unified and computationally efficient approach for solving these problems which takes into account all of the kinematic constraints is developed.     

An evolutionary algorithm for simultaneous localization and mapping (SLAM) of mobile robots

This paper presents a novel algorithm for simultaneous localization and mapping (SLAM) of mobile robots. The algorithm, termed Evolutionary SLAM, is based on an island model genetic algorithm (IGA). The IGA searches for the most probable map(s) such that the underlying robot's pose(s) provide(s) a robot with the best localization information. The correspondence problem in SLAM is solved by exploiting the property of natural selection, to support only better-performing individuals to survive. The algorithm does not follow any explicit heuristics for loop closure, rather it maintains multiple hypotheses to solve the loop-closing problem. The algorithm processes sensor data incrementally and, therefore, has the capability to work online. Experimental results in different indoor environments validate the robustness of the proposed algorithm.     

Welded seam 3D calculation and seam location for welding robot system

Abstract

Using laser scanning techniques, scanning lens rotating around a laser diode and a circular laser trajectory was projected onto the surface of a weldment to detect it. Furthermore, one novel vision sensor based on the circular laser is developed. The three-dimensional (3D), circular laser based seam location sensor is investigated. On the basis of the light path system, 3D calculation algorithm is brought forward and used to locate the welded joint. After image denoise, filter, segmentation and thinning, characteristic points of the welded joint could be detected real time using a proposed vision sensor and confirmed by real experiments of butt welded joints with I groove and V groove, and lap, and fillet and ramp welded joints. The results show that circular laser based vision sensor can be used in seam locating and its calculation precision meets the requirement of seam tracking.     

Error analysis of forward and reverse heat conduction and convection calculations considering uncertainties in welding

Abstract

Numerical models of fusion welding traditionally compute temperature field for a given set of welding conditions in a forward manner. The reliability of computed temperature profile depends on the accuracy of a number of model input parameters, values of which are uncertain in nature. Here, the authors show that a genetic algorithm (GA) assisted integrated numerical model, following either convection or conduction based calculations, can identify the suitable values of the uncertain model input parameters and in turn provide reliable computed results. Powered with GA, the integrated model is used further in a reverse manner to predict multiple sets of welding conditions for a target weld geometry. The convection based calculations have been able to provide more reliable multiple welding variables in reverse calculations.     

MODIFIED GENETIC ALGORITHM APPLIED TO SOLVE PRODUCT FAMILY OPTIMIZATION PROBLEM

The product family design problem solved by evolutionary algorithms is discussed.A successful product family design method should achieve an optimal tradeoff among a set of compet- ing objectives,which involves maximizing commonality across the family of products and optimizing the performances of each product in the family.A 2-level chromosome structured genetic algorithm (2LCGA)is proposed to solve this class of problems and its performance is analyzed in comparing its results with those obtained with other methods.By interpreting the chromosome as a 2-level linear structure,the variable commonality genetic algorithm(GA)is constructed to vary the amount of plat- form commonality and automatically searches across varying levels of commonality for the platform while trying to resolve the tradeoff between commonality and individual product performance within the product family during optimization process.By incorporating a commonality assessing index to the problem formulation,the 2LCGA optimize the product platform and its corresponding family of products in a single stage,which can yield improvements in the overall performance of the product family compared with two-stage approaches(the first stage involves determining the best settings for the platform variables and values of unique variables are found for each product in the second stage). The scope of the algorithm is also expanded by introducing a classification mechanism to allow mul- tiple platforms to be considered during product family optimization,offering opportunities for supe- rior overall design by more efficacious tradeoffs between commonality and performance.The effec- tiveness of 2LCGA is demonstrated through the design of a family of universal electric motors and comparison against previous results.     

Behaviour of Thiosulphate in Electrodialysis in the Presence of Photographic Gelatin

Electrodialysis of a 10 per cent solution of gelatin containing 30 /M of thiosulphate labelled 3,S in the outer sulphur atom was carried out with a brentzinger apparatus. Forty-five per cent of the radioactivity appeared in the anodic liquid, thirty per cent in the cathodic and the remaining twenty-five per cent in the gelatin solution. The validity of these results is discussed also in relation to other experiments carried out with ,SS labelled sulphate and :aP labelled phosphate.     

Numerical simulation of molten metal flow under vacuum condition in high pressure and low pressure die casting process

Abstract

The vacuum analysis algorithm was developed to simulate the total system of high pressure die casting process including vacuum vent, cavity and plunger area. The various vacuum degrees (760, 650, 500, 250 and 60 mmHg) were artificially applied in cavity. The filling behaviours of molten metal under the applied vacuum conditions were simulated and compared with those of experiment. The filling amount in cavity was increased with the increase of applied vacuum pressure during partial shot experiments. The simulated filling behaviours of molten metal were relatively well agreed with those of experiment. Through the results of fluid flow simulation, the relationship of filling length and filling velocity with the variation of vacuum pressure was analysed respectively. And it applied to a real die casting product and the internal gas quantity of product was significantly reduced by modification of vacuum gate system.     

Genetic algorithm for optimisation of A-TIG welding process for modified 9Cr–1Mo steel

Abstract

It is essential to set up the activated tungsten inert gas (A-TIG) welding process parameters to produce the desired weld bead geometry and heat affected zone (HAZ) width in modified 9Cr–1Mo steel weld joints. Therefore, it becomes necessary to develop a tool for optimisation of A-TIG welding process. Genetic algorithm (GA) based model has been developed to determine the optimum process parameters. In this methodology, first independent ANN models correlating depth of penetration, weld bead width and HAZ width with current, voltage and torch speed respectively were developed. Then, GA code was developed in which the objective function was evaluated using the ANN models. There was good agreement between the target and actual values of bead geometry and HAZ width obtained using the GA optimised process parameters. Thus, a methodology using GA has been developed for optimising the A-TIG process parameters for modified 9Cr–1Mo steel.     

Efficient sub-band coding in JPEG2000 for improved authentication and tamper-proofing

Abstract

The LL sub-band from the discrete wavelet transform in JPEG2000 is similar to a smaller image of the original in spatial domain. The proposed authentication and tamperproofing scheme is to extract and hide the entire LL sub-band into the first-level sub-bands, 1LH and 1HL. The hidden data are used later with a unique digital signature and a public key to prove the authenticity of the image. Tampered areas could be accurately detected and recovered to a quality that is visually acceptable. This scheme can be used to authenticate sensitive images, such as medical images, to prove rightful ownership and to recover images before originals are available.