Mozasser Rahman

This paper describes the impedance characteristics of the human arm during passive movement. The arm was moved in the desired trajectory. The motion was actuated by a 1-degree-of-freedom robot system. Trajectories used in the experiment were minimum jerk (the rate of change of acceleration) trajectories, which were found during a human and human cooperative task and optimum for muscle movement. As the muscle is mechanically analogous to a spring-damper system, a second-order equation was considered as the model for arm dynamics. In the model, inertia, stiffness, and damping factor were considered. The impedance parameters were estimated from the position and torque data obtained from the experiment and based on the “Estimation of Parametric Model”. It was found that the inertia is almost constant over the operational time. The damping factor and stiffness were high at the starting position and became near zero after 0.4 seconds.

This paper introduced an Intelligent Salat Monitoring and Training System based on machine vision and image processing. In Islam, prayer (i.e. salat) is the second pillar of Islam. It is the most important and fundamental worshipping activity that believers have to perform five times a day. From gestures’ perspective, there are predefined human postures that must be performed in a precise manner. There are lots of materials on the internet and social media for training and correction purposes. However, some people do not perform these postures correctly due to being new to salat or even having learned prayers incorrectly. Furthermore, the time spent in each posture has to be balanced. To address these issues, we propose to develop an assistive intelligence framework that guides worshippers to evaluate the correctness of their prayer’s postures. Image comparison and pattern matching are used to study the system’s effectiveness by using several combining algorithms, such as Euclidean distance, template matching and grey-level correlation, to compare the images of the user and the database. The experiments’ results, both correct and incorrect salat performances, are shown via pictures and graph for each of the postures of salat.

Point-to-point robotic arm has been used in manufacturing industry to assist company in increasing its production rate. However, the biggest concern in robotic arm is the accuracy for the robot to complete the task of pick-and-place of an object which is dependent on the designed controller. This study investigates the accuracy of the 5 degrees of freedom (DOF) robotic arm model with PID controller. The forward kinematic is analysed systematically in order to determine the required movements for each of the robotic arm joint for its desired operations. The objective of this paper is to simulate the movements of the robotic arm with and without controller by utilizing MATLAB GUI, a microcontroller and servo motors in order to demonstrate the effectiveness of the system. Performance comparison of the robotic arm in completing the pick-and-place task with and without PID is presented in this paper. The preliminary results showed that the difference errors between the desired angular displacement of with and without controller are 0.65%, 3.61%, 10.74%, 82.18% and 44.44% for the five movements.

Utilization of Thermopile sensor at an early stage of human detection is challenging as there are many things that produce thermal heat other than human such as electrical appliances and animals. Therefrom, an algorithm for early presence detection has been developed through the study of human body temperature behaviour with respect to the room temperature. The change in non-contact detected temperature of human varied according to body parts. In an indoor room, upper parts of human body change up to 3°C whereas lower part ranging from 0.58°C to 1.71°C. The average changes in temperature of human is used as a conditional set-point value in the program algorithm to detect human presence. The current position of human and its respective angle is gained when human is presence at certain pixels of Thermopile's sensor array. Human position is estimated successfully as the developed sensory system is tested to the actuator of a stand fan.

This paper presented the development of sensory system for detection of both the presence and the location of human in a room spaces using MEMS Thermal sensor. The system is able to detect the surface temperature of occupants by a non-contact detection at the maximum of 6 meters far. It can be integrated to any swing type of electrical appliances such as standing fan or a similar devices. Differentiating human from other moving and or static object by heat variable is nearly impossible since human, animals and electrical appliances produce heat. The uncontrollable heat properties which can change and transfer will add to the detection issue. Integrating the low cost MEMS based thermal sensor can solve the first of human sensing problem by its ability to detect human in stationary. Further discrimination and analysis must therefore be made to the measured temperature data to distinguish human from other objects. In this project, the fan is properly designed and program in such a way that it can adapt to different events starting from the human sensing stage to its dynamic and mechanical moving parts. Up to this stage initial testing to the Omron D6T microelectromechanical thermal sensor is currently under several experimental stages. Experimental result of the sensor tested on stationary and motion state of human are behaviorally differentiable and successfully locate the human position by detecting the maximum temperature of each sensor reading.

Electromyogram (EMG) generates small signal amplitude upon muscle contraction. It is difficult to distinguish the significance of its EMG response but yet its control feasibility has been proven by many research. In this paper, the feasibility of EMG based artificial hand utilizing conventional EMG sensor was put into study. Instead of performing complex processing which may exponentially increase the cost of EMG artificial hand, the concept proposed in this paper, utilizes simple threshold activation key. The rest of the control specification is dealt with force sensor feedback. From this study, it is proven that using conventional EMG sensor to control an artificial hand is feasible to perform simple task. However, further study is required to enhance the reliability of the system.

Hyper-redundant robot (HRR) manipulators are useful at navigating convoluted paths, but conventionally complicated to control. The control of a hyper-redundant manipulator is complex due to its redundancy. In this paper, a simple but effective control algorithm for obstacle avoidance is proposed. The algorithm derives a collision free path around known obstacles so that the end-effector of a variable length hyper redundant robot (VHRR) is able to reach the target location following the path without hitting the obstacles. The algorithm can be grouped into two tasks to drive the end-effector along the collision free trajectories: first, solve the inverse kinematics without disregarding the existence of obstacles in the system; and second, fit the manipulator to the respective prescribe trajectories. This method has the capability to allow VHRR maneuver within its workspace without penetrating to the neighboring obstruction. Further, this method is very effective in the sense that it forms a nice coil profile avoiding zig-zag configuration, and thus eliminates sharp turn on the robot. The performance of a VHRR was tested through simulation to demonstrate the effectiveness of the proposed method. The approach succeeded in delivering the path that avoids obstacle.

This paper presents the impedance characteristics of human arm in daily spatial activity. Human arm is considered as a mass-spring-damper system. The input data in the form of Cartesian position is measured to get dynamic impedance relationship by the motion equation for the mass-spring-damper system. Mappings are done by various combinations to observe the nature of the different impedance components during dynamic movement. The significant amount of variation in damping and inertia components are observed in every turning of the arm movement while the stiffness shows the changing behavior throughout the movement. From this study it is known that for this particular movement the arm follows a pattern and same behavior is followed for the repetitions of the movement. The obtained result could be beneficial for the study of upper extremity exoskeleton for human rehabilitation.

Mimicking human arm motion has become a challenging topic for the researchers among the field of Human rehabilitation, motor control and perception, biomechanics, and several other related research topics. Considering human-robot cooperation, this paper is focused on modeling human arm while performing planner motion. In this work human arm is assumed as a mass-spring-damper system and based on this assumption the related mathematical model is developed. The desired movement in this study is one of the daily activities with obstacle. Mathematical model is developed with the help of the robotic principle, mechanical system analysis method, and also with the help of biological data. The kinematic and dynamic data is then analyzed. In this work kinematic data are taken from the ShapTape® device. The different components of the position, velocity and acceleration are compared. Besides, the analysis of the simulated torques is done. MATLAB is used for the simulation. These observations are expected to give several ideas for designing a controller for upper limb exoskeleton for rehabilitation purposes.

Level Crossing Control: A Novel Method Using Sound Recognition