A path planner enabling second-order continuity across multiple motion modes of the generalized bicycle model

Abstract

In mobile robotics, the generalized bicycle model is notable for its agility and diverse motion capabilities. However, current path planning methods often overlook its potential for multiple motion modes, leading to impractical paths and collision risks in complex environments. To address this, our study introduces a novel path planning algorithm that utilizes the generalized bicycle model and ensures second-order continuity, crucial for smooth and safe navigation. We establish rigorous second-order continuity conditions for seamless motion mode transitions and derive criteria for each mode. Our algorithm integrates these conditions with the rapidly exploring random tree concept to generate optimal paths that accommodate the model’s mode-changing capabilities. Through tests in challenging environments, our method demonstrates improved performance, especially in narrow passages, enhancing path planning safety and efficiency for mobile robots. This advancement significantly contributes to the field of robotic path planning by offering a more dynamic and reliable approach to autonomous navigation.