Development of Artificial Intelligent Techniques for Manipulator Position Control

Inspired by works in soft computing this research applies the constituents of soft computing to act as the "brain" that controls the positioning process of a robot manipulator's tool. This work combines three methods in artificial intelligence: fuzzy rules, neural networks, and genetic algorithm to form the soft computing plant uniquely planned for a six degree-of-freedom serial manipulator. The forward kinematics of the manipulator is made as the feedforward control plant while the soft computing plant replaces the inverse kinematics in the feedback loop. Fine manipulator positioning is first achieved from the learning stage, and later execution through forward kinematics after the soft computing plant proposes inputs and the iterations. It is shown experimentally that the technique proposed is capable of producing results with very low errors. Experiment A for example resulted the position errors onpx: 0.004%;py: 0.006%; andpz: 0.002%

Using Worn Out Insole To Express Human Foot

The human foot is unique, which is evident in its print. The purpose of this work was to determine the foot's work volume given a footprint. Five volunteers participated in the study who supplied their used shoes. The insole images were processed to find the effective regions. The correct spots were identified and were marked. The drawn footprints looked similar geometrically; however, each footprint had a different node positions profile. The aspect ratio of the foot length, width, and height congregated to 3:1:1, and the footprint angle was 30 degrees. The actual plots revealed that the ranges of the foot length ratio and the footprint angle were 2.20 to 3.00, and 30 degrees to 45 degrees, respectively. Therefore, the human foot identity may be expressed by simple measurements of the foot height, the foot width, the foot height following the standardised node locations

Representing System by Gene Encoding

The chromosomes that belong to the parents store genetic information. The child inherits the information through uniquely selective procedures. Using the concept, this study proposes an approach to system representation using the process found in genetic information inheritance. A generic process flow to building the representation is shown in the form of ladder-like flow chart that has the starting point at the bottom. This forms the basis for gene encoding. Following this process flow, one can expect to represent a system which requires solutions from selective procedures. Therefore, the codes written may vary depending on how one models and interprets the representation

Experimenting With The Problem-Based Learning

Departing from traditional approach to a new one in teaching practice is not easy. Being a new university that subscribes to even newer teaching practice results complication. The teaching staff are trained within traditional teaching boundary, whom are relaxed by the approach for teaching that they have accustomed to. The problem-based learning or PBL is not a new teaching practice. Only a few institutions of higher learning implement this approach such as the Temasek Polytechnic, Singapore; and Tromso University College, Norway. Based on the successes of these institutions, we choose to experiment PBL into our academic settings. The respondents comprise of 50 second-year students and 53 final-year students. Using both qualitative and quantitative research methods, and making this experiment's scope only to analyzing students' feedbacks while undergoing the course, this paper explores approaches, methodology, and ways into which PBL may be implemented effectively in the future. Improved topic understanding, team-working, independent were some of the positive feedbacks on the PBL approach. On the contrary, PBL was said to be good for individual work rather than grouping and too much time was spent for every session. In addition, around 60% of respondents agree that PBL stimulates thinking more spontaneously, induces a refreshing change from the routine classroom lessons, and contributes to the depth of learning

Review on EMG Acquisition and Classification Techniques: Towards Zero Retraining in the Influence of User and Arm Position Independence

The surface electromyogram (EMG) is widely studied and applied in machine control. Recent methods of classifying hand gestures reported classification rates of over 95%. However, the majority of the studies made were performed on a single user, focusing solely on the gesture classification. These studies are restrictive in practical sense: either focusing on just gestures, multi-user compatibility, or rotation independence. The variations in EMG signals due to these conditions present a challenge to the practical application of EMG devices, often requiring repetitious training per application. To the best of our knowledge, there is little comprehensive review of works done in EMG classification in the combined influence of user-independence, rotation and hand exchange. Therefore, in this paper we present a review of works related to the practical issues of EMG with a focus on the EMG placement, and recent acquisition and computing techniques to reduce training. First, we provided an overview of existing electrode placement schemes. Secondly, we compared the techniques and results of single-subject against multi-subject, multi-position settings. As a conclusion, the study of EMG classification in this direction is relatively new. However the results are encouraging and strongly indicate that EMG classification in a broad range of people and tolerance towards arm orientation is possible, and can pave way for more flexible EMG devices

How electromyography readings from the human forearm are made cryptic, trivial, or non-trivial information for use in synthetic systems

The success of reading potentials generating from human muscle activities is evident that proves that the human body’s neural system is naturally electronics. Now, modern engineering is accepting it as one field of engineering science. Due to this, the concept of a cyborg is beginning to realize as products such as exoskeletons and neuroprostheses. The object of this work, however, is to view from a different perspective as to how this is beneficial to the functions beyond the mentality of today’s applications. We hypothesized that the recorded potentials from muscle activities may be regarded similar as to the signals that jump between synapses in the biological neurons. We suggest that these signals, instead of mere electrical in nature, their waveforms might include emotion characteristics from uniquely combined muscle activities and feeling. The system codes the signals where the newly created information may be made cryptic, trivial, or nontrivial depending on how they are going to be utilized in the synthetic systems. So that the artificial system could sense, for instance, the emotion of the human host

The Classification of EMG Signals with Zero Retraining in the Influence of User and Rotation Independence

The surface electromyogram (EMG) contains information directly related to muscle contraction and modern classification techniques can obtain near-zero error when identifying various gestures over the forearm. However, good results come at a compromise over the ease of use. Once the EMG classifier trained on a user is changed, the accuracy rate will be greatly reduced. Furthermore, changing the position of the forearm also causes drop in accuracy rate. Acknowledging the limitations of EMG classification, this study aims to investigate the EMG signals based on the gestures, and evaluate if there are any gestures which are inherently robust to these variations. The EMG of forearm gestures have been classified in the combined influence user independence, rotation independence and hand exchange independence. Experiment results on 20 participants indicated that truly independent classification can be achieved for most forearm gestures (up to 100%) in some arm positions. Hand exchange is also not feasible as the study has shown that the data field for both hands are fairly different. Out of the nine gestures under study, only the wrist extension was found to be truly independent of all the influences

Determining Foot-Ankle Mechanism Design by Mapping the Relationships Among Bones, Joints, and Ground Reaction Force

This work investigates the following questions—why the bones and the joints are arranged in that way, why it is different from other primates, and how could it be imitated to develop a foot-ankle mechanism. Mathematical models were developed and were based on the relationship among the anatomy of bones and joints, the normalized ground reaction forces that acted on certain nodes on the footprint. Using the model, a custom design prosthetic foot was assembled. It was tested on a robot arm that simulated a walking gait. The stance phase cycle performed on the prototype, and the commercial feet were completed within approximately 1.08 seconds and 1.38 seconds, respectively. The techniques used, however, may require further studies because the prototype foot was not tested on patients. At this stage, the techniques are sufficient to justify that the prototype foot design should consist of an ankle-foot mechanism and a flexible keel. Therefore, proper mappings of bones and joints; and modeling of foot biomechanics is found useful in design and development of prosthetic feet activities

Application of Soft Computing to Serial Manipulator Kinematic Problems

Inspired by the techniques in artificial intelligence, this research applies the constituent of artificial intelligence to perform manipulator positioning tasks. This work combines three methods in artificial intelligence: fuzzy rules, neural networks, and genetic algorithm to form the control block specifically designed to solve kinematic problems of a six degree-of-freedom serial manipulator. The direct kinematic of a manipulator is taken as the feed forward control and the artificial intelligence control block replaces the inverse kinematics when the reverse solving is done. Fine manipulator positioning is achieved from the learning stages executed by the artificial intelligence control block. It is shown experimentally that the technique proposed was capable of producing results with very low errors

Analysis of unimorph piezoceramic patches on damped square shaped plate

Active damping using piezoelectric element is one of the effective techniques to counter vibration problems. A 3D finite-element model is developed as part of investigation for damping control. The piezoelectric patches are surface bonded on quadrilateral thin plate and supported with spring damper elements. The main goal of this paper is to investigate mechanical characteristics of piezoceramic array on membrane and the effect of force excitation using small motor and electric excitation on the system. The system setup produced small vibration displacement and does not displace the plate beyond elastic strain region. The results show the linear behavior of piezoceramic and the correlation between electric excitation, motor vibration and displacement at the centre of the plate at different frequency range. The mode shapes and natural frequencies at low frequency spectrum are also presented. Therefore, the results can be used as reference to develop damping system with aid of piezoelectric patches