Real-Time Path Planning and Collision Avoidance for Hybrid Kinematic Systems

Abstract

In the rapidly evolving field of autonomous systems, the integration of real-time path planning and collision avoidance remains a critical challenge, particularly for hybrid kinematic systems that combine discrete and continuous dynamics. This paper presents a novel approach to real-time path planning and collision avoidance specifically tailored for hybrid kinematic systems. We propose an adaptive path planning algorithm that leverages a hybrid model combining both heuristic and optimization techniques to ensure efficient and effective navigation. Additionally, we introduce a collision avoidance mechanism based on dynamic safety zones and predictive control, which allows for rapid adjustments to avoid potential collisions in complex environments. The performance of the proposed methods is evaluated through extensive simulations in various scenarios, demonstrating significant improvements in both path optimality and computational efficiency compared to existing approaches. Our results indicate that the proposed techniques can successfully handle the intricacies of hybrid kinematic systems, providing robust solutions for real-time operation. The findings offer valuable insights and practical contributions to the development of autonomous systems operating in dynamic and unpredictable environments.