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This paper proposes a strategy for bipedal robot walking on inclined surfaces using position and orientation based inverse kinematics algorithm. Some researchers implemented control approaches to solve bipedal walking on inclined surfaces. Generally, most of them apply control feedback at ankle joints and also introduced many more control methodologies. In this paper, inverse kinematics methodology is introduced systematically for bipedal walking on inclined floor. Positions and orientations are embedded into the kinematics calculation. In this strategy, a working bipedal robot walking pattern for flat floor must be developed first. Then, the same walking pattern can be used for the inclined floor with orientation included so that the bipedal robot is able to walk on the inclined floor successfully. This methodology will distribute the angles caused by the inclined surfaces to the appropriate robot joints. By doing this, control at ankle joints only is avoided. A 3-D dynamics simulator which is known as Robot Control Simulator and developed in our laboratory is used for simulation in order to validate our proposed method.

Purpose of the study: To evaluate the efficacy of a CAI called MathTutor in helping autistic students to learn addition in mathematics. Methodology: A pre-post-test experimental model was employed in the study. The study participants included three autistic male students who possessed all the prerequisite skills. Main findings and novelty: The study participants were found to have been benefitted which indicates that MathTutor improves their learning abilities as an effective instructional strategy. The use of CAI enabled the participants to memorise their lessons and actively take part during the entire lesson. Applications of this study: The study is beneficial for people involved in caring for autistic students with the help of computer assisted application. This will ease the burden of the carer takers of autistic children in dealing with their conditions while at the same enabling them to navigate the world.

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The objective of this paper is to design a controller which is able to control the output angle for an upper limb of a robotic arm, for precision motion and high speed response.  The aim is to optimize the best controller for an upper limb robotic arm system for precision motion, in which improper motion will results in injuries/ fatality and loss of production in manufacturing system. In this research, a robotic arm prototype with a 1 degree-of-freedom (DOF) was designed and fabricated, in which the DC geared motor was implemented.  Studies are carried out based on previous research to investigate the suitable type of controller. PID controller and fuzzy logic controller are chosen and compared in terms of their performances such as the steady-state error, settling time, rise time and overshoot. The equipment’s used are Micro-Box 2000/2000C, Cytron DC geared motor, motor driver circuit. Micro-Box module acts as the interface between hardware component and MATLAB R2009a. Open-loop simulations are carried out to obtain the transfer function of the motor and substituted into the system for further simulation analysis. Simulation for the uncompensated system is carried out to observe the close-loop system characteristic without the controller. After that, the close-loop point-to-point (PTP) trajectory control for simulations & experiments are carried out for the compensated systems using PID controller based on the Ziegler-Nichols frequency response method. Analyses are made based on the results obtained and the best type of controller is chosen for achieving precise motion control for the upper limb robotic arm. In this paper, the PID controller shows better performances compared to the Fuzzy Logic controller (FLC) with the steady state error of less than 0.010 and settling time of 0.5s; for the input reference of 150  respectively.