Study on Omnidirectional Cooperative Trasnport System Using Multiple Dual-wheeled Mobile Robots with Active-Caster Control

In this paper, we propose a omnidirectional transport system with multiple dual-wheeled mobile robots and a LiDAR-based robot self-orientation estimation method. The proposed transport system applies active caster control to the dual-wheeled mobile robots, enabling them to move the transport object in all directions. The orientation of the robot with respect to the object is very important in control of the robot used in this system. To estimate the orientation of the robot immediately, we propose a method to measure inner substructure of the object using LiDAR and estimate the orientation from a point cloud. In proposed method, the orientation is estimated from vertex location information obtained from the point cloud, and most of the points in the point cloud are not directly used for orientation estimation. Although this method cannot perform localization and mapping like SLAM, it is effective than SLAM in terms of computation time in estimating an orientation of an object in an invariant environment and position in the environment, as in our transport system. Through experiments, we confirmed that this estimation method works effectively in the proposed conveyance system.