Control in Robotics and Autonomous Systems in Nigeria: Current Landscape, Challenges, and Strategic Pathways

Abstract

This article looks at control systems in robotics and autonomous systems (RAS) within Nigeria. Despite worldwide progress in feedback control, optimal estimation, and learning-based autonomy, Nigeria's RAS sector is still developing. It's marked by scattered research, minimal industrial use, and inadequate infrastructure. We review various control methods, including PID, LQR, MPC, and adaptive control, and evaluate their relevance to Nigerian applications, such as agricultural drones, self-driving cars for road safety, pipeline monitoring, and medical robotics. By combining a literature review with expert surveys (n=30), we uncover key obstacles: unreliable power supply, no local sensor production, weak connections between universities and industries, and a lack of national RAS standards. While Nigerian researchers show solid theoretical understanding (over 70% familiarity with PID and MPC), the practical application is under 10% due to hardware limitations. A comparative table of control methods against application readiness is included. We conclude that a phased plan, starting with inexpensive embedded control for agriculture and progressing to durable off-grid autonomy, is crucial. Recommendations include a national curriculum for control systems, public-private testbeds, and regulatory frameworks for certifying autonomous systems.