A Novel Platform Orientation System for Proportional-Integral-Derivative-Controlled Ball-Catching Robot

Abstract

Abstract Ball catching by a robot is one of the challenging and complex control tasks that is extensively studied to achieve human-like skills in robots. Over the last decade, several ball-catching robot designs have attained benchmarks in visual tracking and control algorithms. However, the coordination between the ball’s path tracking and the robot’s motion planning remains highly sensitive to environmental parameter changes. In general, ball-catching robots require a noise-free background with good lighting and multiple off-board tracking cameras. Also, a common failing point of these systems is the short flight time (or high-speed) of the ball and the uncertainties of throwing direction. To address these issues, in this study, we propose a ball-catching platform system that can rapidly orient the platform towards the throwing direction by utilizing two onboard cameras with multi-threading. A graphical user interface platform has been developed to implement the orientation algorithm and mask the ball with high accuracy. Our experimental results show that the proposed orientation platform system can be used in a low-light noisy background, and the overall ball-catching rate increases from 50% to 90% compared to the baseline design. The new system can also avoid erratic platform movements when masking is done in a noisy environment.