About the Project

Industry 5.0 has emerged as the next wave after Industry 4.0. The emergence of Industry 4.0 has revolutionised the manufacturing sector, leading to the integration of advanced technologies such as robotics, automation, and artificial intelligence. While Industry 4.0 focuses on optimisation and efficiency through technology, Industry 5.0 aims to reintroduce the human element into the equation. In this context, cooperative robots will collaborate with humans to perform complex tasks to improve productivity, flexibility, and efficiency. However, achieving seamless cooperation between robots and humans in a dynamic and uncertain environment poses numerous challenges that need to be addressed. Model Predictive Interactive Control (MPIC) presents a promising approach to tackle these challenges and optimise the performance of cooperative robotic systems in Industry 5.0 settings.

This research aims to explore the application of MPIC techniques to enhance the cooperative capabilities of robots and enable efficient coordination and decision-making in real-time scenarios. The proposed work should consist of designing a novel MPIC framework that optimises the cooperative behaviour of multiple robots with humans while considering system dynamics, constraints, and coordination objectives. The project objective is to develop an algorithm for trajectory planning, obstacle avoidance, collision detection, and task allocation within the cooperative robotic environment. Comprehensive simulations should be conducted to evaluate the performance of the proposed MPIC framework, by implementing the framework on a real-world multi-robot industrial setup to validate its effectiveness, robustness, and scalability.

The developed model predictive interactive control algorithms will enable more efficient coordination, optimisation, and adaptability of multiple robots working collaboratively with humans in industrial settings. The research outcomes will benefit industries by enhancing productivity, reducing downtime, improving resource allocation, and enabling the effective integration of cooperative robotic systems within the Industry 5.0 framework.

Funding Notes

there is no funding for this project