Path Planning of SCARA Robot using RRT* Algorithm

From the early 1950s to the present day, "Robot" has become one of the most common words in our daily lives. Today, robots are used for surgery, massage therapy, space exploration, manufacturing, and code analysis, but the earliest robots were far more primitive - they were tools that could tell time or automatons that could perform for entertainment. Broadly defined, humans have been developing robotics and automata for hundreds of years. Research is continuously being conducted to make these robots more and more suitable and flexible for their workplace. There are several sectors of robotics. Among them, manipulator path planning or trajectory generation has always been a key field of interest for many researchers. In this study, the Rapidly Exploring Random tree (RRT) and RRT* algorithm were used along with the typical cubic spline method for manipulator trajectory generation in a complex environment to generate the optimal path avoiding obstacles. A robotic manipulator with three degrees of freedom was designed to conduct the research work. The kinematics model of the manipulator was set up using the D-H parameters method. The effectiveness of kinematics equations was verified by the Robotics Toolbox simulation of MATLAB. For better evaluation of the generated path, the workspace of the manipulator was also analyzed via the Monte Carlo method. The analysis results showed whether the manipulator’s working space is well-knit and whether this method is feasible or not, which laid the foundation for the study of trajectory planning and motion control. To validate the analytical model of the manipulator, it was compared to the model simulated in the simulation environment of MATLAB using the Robotics toolbox and was also validated by experimenting in a real-world scenario.