Artificial Intelligence (AI) stands at the intersection of unprecedented opportunities and profound challenges. As AI is increasingly integrated into societal structures, the necessity for transparency and open-source approaches becomes paramount to foster both innovation and ethical considerations. Collaborative efforts among academia, industry, and policymakers are essential for addressing the multifaceted complexities that AI presents. While AI promises transformative benefits, potential challenges, such as its weaponization, corporate exploitation, and job displacement, warrant careful attention. Striking a balance between regulation with innovation is critical. Academic institutions can play a pivotal role, guiding AI’s trajectory, nurturing interdisciplinary learning, and equipping future professionals. Embracing open-source AI can ensure its ethical use and mitigate the risks associated with its exploitation. The existential threats posed by AI are significant, yet with strategic collaboration and foresight, a bright, AI-driven future is within reach.

Robots that can comprehend and navigate their surroundings independently on their own are considered intelligent mobile robots (MR). Using a sophisticated set of controllers, artificial intelligence (AI), deep learning (DL), machine learning (ML), sensors, and computation for navigation, MR's can understand and navigate around their environments without even being connected to a cabled source of power. Mobility and intelligence are fundamental drivers of autonomous robots that are intended for their planned operations. They are becoming popular in a variety of fields, including business, industry, healthcare, education, government, agriculture, military operations, and even domestic settings, to optimize everyday activities. We describe different controllers, including proportional integral derivative (PID) controllers, model predictive controllers (MPCs), fuzzy logic controllers (FLCs), and reinforcement learning controllers used in robotics science. The main objective of this article is to demonstrate a comprehensive idea and basic working principle of controllers utilized by mobile robots (MR) for navigation. This work thoroughly investigates several available books and literature to provide a better understanding of the navigation strategies taken by MR. Future research trends and possible challenges to optimizing the MR navigation system are also discussed.