Dynamic Obstacle Avoidance with Enhanced Social Force Model and DWA Algorithm Using SparkLink

In the context of Industry 4.0, addressing the challenge of dynamic obstacle avoidance for Automated Guided Vehicles (AGVs) in complex industrial environments, this paper proposes an algorithm that integrates an enhanced social force model (SFM) and an improved dynamic window approach (DWA), leveraging SparkLink communication technology to enhance data transmission speed and reliability. The introduction of SparkLink technology significantly improves the environmental perception capabilities of AGVs, optimizing their dynamic obstacle-avoidance performance. Experimental results demonstrate that this method effectively increases the efficiency of AGVs in dynamic obstacle avoidance, offering significant practical value.