This research work presents the design of a position control algorithm for trajectory tracking of a four-degree-of-freedom robotic manipulator. The linkage mechanism of the manipulator is based on a parallelogram mechanism and in this manipulator, three parallelogram mechanisms are used. First, the CAD and the kinematic model of the manipulator are developed. The bond graph (BG) approach is applied to develop the dynamic model of the robotic arm based on kinematic equations. The BG model of parallelogram linkage is then compared with the Simulink model of parallelogram linkage and results are validated. Then, a position control algorithm is proposed to follow a set of trajectory planning applications. A GRBL-Arduino based controller is used to estimate the position of the end-effector as per the user's requirements. The simulation and experimentation work are performed for 3D trajectory tracking applications. The robotic arm is used for pick and place operation within the workspace.

For any robot to navigate on its own, it is important to create a map of its surroundings and localise itself to detect the obstacles. The present paper focuses on building a universal robotic description format model for the TETRIX robot followed by optimisation of 2D simultaneous localisation and mapping parameters using genetic algorithm in ROS-based environment to make robot navigation efficient. The GMapping and adaptive Monte Carlo localisation parameters were optimised using multiobjective GA. Furthermore, map quality is validated by using no reference blind/referenceless image spatial quality evaluator factor. The statistical analysis based on the mean and standard deviation of particle filters was analysed to measure the spread the particles filters during localisation. The test environment was created in ROS, Gazebo and MATLAB and with optimal parameters good quality high-resolution map with accurate and efficient localisation was achieved.

This study postulates applicable and high-performing solutions for the inverse kinematic (IK) problem of two-segmented robotic arm using algebraic models. The former section of models is acquired from the manipulation of trigonometric rules, specifically the sum and Pythagorean identities to solve the second joint angles. The latter part of models is drawn by exploiting a matrix mechanics called Cramer's rule for the results of first joint angle. For verification, the precision of solutions yielded are cross-checked with the manipulator's direct kinematics and tested with the statistical measure of minimum square error while tracking cubic Hermite spline, cubic Bezier, cubic B-spline, ellipse and circle curves. For validation, a spreadsheet-based IK application utilising built-in front-end capabilities including Visual Basic for applications, Math and Trig function library, name manager, data validation, ActiveX controls, and charts is developed to accommodate these models and simulate the feasible joint angles and orientations of robotic arm.

This study developed an automated tableware tidying-up robot mechanism to tidy up the tableware in a self-service restaurant with a large number of tableware. This study focused on the process of sorting and collecting tableware that were placed on trays by the guest and flowed to robot with belts conveyor. The separated tableware was placed in a washing machine. Garbage and leftover food were also treated with this robot mechanism. The parallel arm and robot hand mechanism were designed to realise the advantages of low cost, high processing speed, and space saving. It was proved that the prototype robot can move and grab tableware smoothly with the high-speed position control. The finger and hand rotation mechanism can throw away leftover food by the leftover food throwing experiment. Additionally, the system can sort the tableware by multiple robots was verified using the tableware sorting experiment.