Tuesday 25 February 2025
Scientists have been working on a new way to improve the accuracy of robots that work together in manufacturing processes. These multi-robot systems are designed to perform tasks such as assembly and welding, but their performance can be limited by the uncertainty of their joint movements.
To overcome this challenge, researchers have developed an adaptive model predictive control (MPC) system that takes into account the uncertainties of the robot’s joints and the coupler geometry. The system uses a differential-algebraic equation (DAE) model to simulate the behavior of the robots and estimate the uncertain kinematic parameters in real-time.
The MPC system is designed to optimize the joint trajectories of the robots, ensuring that they work together smoothly and accurately. The algorithm adjusts the control inputs based on the estimated uncertainties and the measured torques from the sensors.
In a recent study, scientists tested the adaptive MPC system on two industrial robots connected by a coupler. They created a reference trajectory for the robots to follow, but added vibrations to simulate real-world disturbances. The results showed that the adaptive MPC system was able to track the reference trajectory with high accuracy, even in the presence of uncertainties and disturbances.
The researchers used a sensitivity analysis to estimate the uncertain kinematic parameters of the robots and coupler geometry. They found that the estimated parameters were accurate enough to improve the performance of the MPC system.
The study demonstrates the potential of adaptive MPC systems for improving the accuracy of multi-robot systems in manufacturing processes. The technology has applications in various industries, including aerospace, automotive, and healthcare.
In the future, scientists plan to further develop the adaptive MPC system and test it on more complex robotic systems. They also aim to explore new applications for the technology, such as in human-robot collaboration and autonomous vehicles.
The development of adaptive MPC systems is an important step towards creating more accurate and reliable multi-robot systems. As robotics continues to play a vital role in manufacturing and other industries, this technology has the potential to make a significant impact on the field.
Cite this article: “Improving Multi-Robot System Accuracy with Adaptive Model Predictive Control”, The Science Archive, 2025.
Robots, Manufacturing, Adaptive Mpc, Uncertainty, Joint Movements, Coupler Geometry, Differential-Algebraic Equation, Model Predictive Control, Multi-Robot Systems, Robotic Accuracy.
