Trajectory planning and tracking are the most important aspects of mobile robot research for industrial application. In this research, an intelligent hybrid control is presented to enhance the usability of mobile robots in environments cluttered with static obstacles. The control is hybrid in two ways. On one hand, the algorithm combines obstacles avoidance and trajectory generation. The generated trajectory acts as a reference path to be followed by the mobile robot. On the other hand, the algorithm not only generates trajectory but also tracks the generated trajectory. An optimizationbased intelligent algorithm, simulated annealing, is designed to plan and generate a trajectory for collision-free robot motion in an environment with stationary obstacles. The PID (Proportional-Integral-Derivative) control algorithm is designed to track the generated trajectory with minimum error. Both algorithms are hybridized such that the generated trajectory becomes a reference trajectory for the tracking control algorithm. The simulated annealing generates a realistic trajectory that consists of a series of the best points with obstacles on the path. The best point is selected with the shortest distance from the robot's destination. These points are selected one from each of the grids, generated between the start and destination point of the robot motion. The dimensions of the robot are considered and included in the obstacles dimension to reduce the dimension complexity of the robot. The effectiveness of the proposed hybrid technique is tested in simulation and in real-time experiments for seven types of cluttered environments. The environments vary with size, shape, placement and arrangement of the obstacles. The results show that the simulated annealing generates a collision-free trajectory intelligently without trapping in local minima in these cluttered environments while the PID control tracks the reference trajectory with a maximum absolute error of 0.2 mm. Hence, the proposed method enhances the usability of mobile robots in environments cluttered with static objects.

Mobile Manipulators (MM) has attracted a lot of researchers for incorporation in the robotics field owning to their multitude of applications in real world. Welding automation has its wide applications in industry like automobile manufacturing and power generation industry involving spherical tanks. The objective of this study is to design workspace and devise a methodology to plan position trajectory of welding tool that produces smooth welding while the mobile platform turns simultaneously. The robot proposed in this paper has the manipulator mounted on a platform moving as a turntable to increase the workspace and enhances the mobility of the manipulator. The earlier produces linear segment of weld while the later produces parabolic segment. The kinematic equations for mobile platform and the mounted manipulator are described in detail. The workspace of the robot is visualized based on computations of transformation matrices and jacobians structured based on kinematic equation. Trajectories for each joint, computed using inverse kinematic equations, are also presented. For spherical trajectories the solution of system equations is combined with constraint values for each manipulator joint, thus allowing computation of desired joint position at any time interval. The efficacy of the proposed methodology for the trajectory planning is tested through a case study. The simulation results of motion transformation, workspace and trajectory show that linear segments of the trajectory combine with parabolic trajectory segments smoothly with zero acceleration within designed reachable workspace. The experimental results verify the efficacy of application of presented kinematic and inverse kinematic models for welding of spherical objects.