ROS Based Real-Time Motion Control for Robotic Visual Arts Exhibit Using Decawave Local Positioning System

In this work, we address the problem of real-time control and localization of an autonomous art exhibit designed using Mecanum wheeled omnidirectional mobile robots. Currently, the exhibit is animated using open-loop control as there are no practical means of implementing a localization system in art galleries. This paper proposes a nonlinear model predictive controller (NMPC) supported by a Decawave localization system for trajectory tracking of the robots. A Robot Operating System (ROS) based NMPC is implemented to control the motion of the robot for a smooth and drift-free trajectory tracking. The Automatic Control and Dynamic Optimization (ACADO) toolkit is used to find the optimal control action while considering all constraints on system states and inputs. A Local Positioning System (LPS) is implemented using Decawave 1001 modules to provide position feedback with an Optitrack motion capture system providing ground truth information for validation. The proposed control approach is first evaluated using the Virtual Robot Experimentation Platform (V-REP), which additionally provides means of trajectory design and simulation of the robot in the desired exhibition space. Thereafter, laboratory experiments are conducted to evaluate the performance of the proposed control and localization systems. The results show a smooth and drift-free performance of the system with less than 10% error of the robot size, which can be deployed at gallery spaces with minimal setup requirements.