Fusion of robotics and deep learning for gamified rural landscape design: toward intelligent interaction

Abstract

This study presents a gamification design framework for rural landscapes that integrates deep learning and robotics to enhance interactivity, intelligence, and sustainability. The framework employs deep learning models for semantic segmentation and ecological feature extraction from remote sensing data and utilizes generative adversarial networks (GANs) to generate diverse landscape scenarios, achieving precise modeling and data optimization. Robotics technology amplifies dynamic interaction and user experiences in rural landscapes through functionalities like path planning, voice interaction, and behavior recognition. Additionally, gamification elements such as virtual reality (VR) and augmented reality (AR) are incorporated to stimulate user engagement and foster a sense of connection through activities focused on ecological conservation, cultural heritage, and educational entertainment. Experimental results confirm that the proposed framework significantly improves task completion rates and user satisfaction, offering innovative solutions and technical support for intelligent rural landscape upgrades and rural revitalization.