Collaboration Robotics in Challenging Work Sites Using an Adaptive Genetic Algorithm

The study proposes the use of micro-robots that are capable of collaborating and adapting in challenging and hazardous environments to replace human operators. Collaborative algorithms optimize mobility and collaboration within the cluster, reducing the need for human intervention. This approach significantly reduces losses in terms of human lives, finances, and resources that are associated with human intervention in hostile environments, such as natural disaster sites, potentially hazardous areas, and industrial bases. It also enhances efficiency and speeds up operations, which is crucial in emergencies. However, it is essential to ensure that robotic machines with a given payload are designed and programmed to operate safely in such environments to prevent unintended consequences where tasks are classified as NP complex. Adaptive approaches can potentially make emergency response and industrial operations safer and more efficient. Genetic algorithms are the best choice as a method used for this purpose.