Adaptive Control Strategies for Autonomous Robotic Systems in Dynamic Environments

Abstract

This research proposes a novel adaptive control strategy aimed at enhancing the stability, responsiveness, and adaptability of autonomous robotic systems in dynamic and unpredictable environments. Traditional control methods, while effective in controlled settings, often lack the flexibility required to handle real-time environmental changes, such as varying obstacles, shifting terrain, and sensor noise. The presented approach enables real-time parameter adjustments, ensuring that the system maintains accurate trajectory tracking and stability under changing conditions. Simulations demonstrate that the proposed strategy outperforms both conventional and alternative adaptive control methods in terms of stability, computational efficiency, and robustness to sensor noise. While the current evaluation is based on simulations, future work will focus on implementing this strategy on physical robots to further assess its practical applicability. This adaptive control approach offers promising potential for applications in complex, real-world environments where robotic systems must operate with high levels of autonomy and resilience.