New design of smooth PSO-IPF navigator with kinematic constraints

TL;DR

This paper introduces SPSO-IPF, a novel hybrid path-planning method combining PSO and PF techniques to generate smooth, collision-free paths for mobile robots in static and dynamic environments.

Contribution

The paper presents a new hybrid algorithm, SPSO-IPF, that improves path smoothness and safety by integrating PSO and PF methods for robotic navigation.

Findings

SPSO-IPF produces smoother paths than traditional PSO or PF methods.

The proposed method outperforms existing techniques in static and dynamic environments.

SPSO-IPF demonstrates better safety and efficiency in robot navigation.

Abstract

Robotic applications across industries demand advanced navigation for safe and smooth movement. Smooth path planning is crucial for mobile robots to ensure stable and efficient navigation, as it minimizes jerky movements and enhances overall performance Achieving this requires smooth collision-free paths. Partial Swarm Optimization (PSO) and Potential Field (PF) are notable path-planning techniques, however, they may struggle to produce smooth paths due to their inherent algorithms, potentially leading to suboptimal robot motion and increased energy consumption. In addition, while PSO efficiently explores solution spaces, it generates long paths and has limited global search. On the contrary, PF methods offer concise paths but struggle with distant targets or obstacles. To address this, we propose Smoothed Partial Swarm Optimization with Improved Potential Field (SPSO-IPF), combining both approaches and it is capable of generating a smooth and safe path. Our research demonstrates SPSO-IPF's superiority, proving its effectiveness in static and dynamic environments compared to a mere PSO or a mere PF approach.