Slam Based Robot Find Target EV to Plugin in Complex Environment

Electric vehicle (EV) charging in complex environments presents significant challenges, precise and adaptable interaction between robotic systems and vehicle charging plugs. This paper introduces a novel approach utilizing Simultaneous Localization and Mapping (SLAM) integrated with a robotic arm to facilitate autonomous charging. Methodology used SLAM techniques to enable the robot to accurately perceive and navigate dynamic and cluttered environments. The robotic arm, equipped with sensors and actuators, is guided by this precise environmental mapping to engage charging ports on a diverse range of vehicle models without human intervention. Implementation of the robotic system, including the integration of a vision-based kick algorithm that ensures robustness and adaptability in real-time obstacle detection and navigation. 3D simulations scenarios and robot to vehicle(R2V), robot 2 robot(R2R),robot to everything(R2X) communication demonstrating significant improvements in operational efficiency and adaptability compared to traditional charging solutions. Robot, IOT and EV charging applications increase autonomy and efficiency in electric vehicle infrastructure, high level of safety, economically benefits and monitoring techniques.