Maxwell Hinson

UC Santa Barbara
Chemical Engineering

Robotic Arm Simulator and RRT Motion Planning

The use of autonomous robots has become widespread, and their applications include repairing space shuttles, military vehicle servicing, and even household cleaning. Our research involves studying motion planning algorithms that allow robots to perform specific tasks without human supervision. In this project, we used MATLAB to program an interactive three-dimensional simulation for a three-link robotic arm. This simulation utilizes the Rapidly-exploring Random Tree (RRT) algorithm to plan a path for the arm. Using this motion planning algorithm, the arm is able to reach user-specified goals while avoiding user-specified obstacles. This simulation will function as a teaching tool, allowing students to better understand how the RRT algorithm works. In addition, we have explored methods of optimizing the path, such as path smoothing, in order to minimize the distance that the robotic arm needs to travel.

UC Santa Barbara Center for Science and Engineering Partnerships UCSB California NanoSystems Institute