Urban green spaces such as parks and gardens are indispensable in both virtual and real-world environments. Therefore, planning such spaces is highly valuable. While scene synthesis literature has limited interest in this topic, many existing parametric design and procedural content generation approaches can be adapted to generate urban green spaces. However, these approaches heavily rely on manual work or are prone to producing monotonously repeated objects. This paper presents a framework that can automatically plan urban green spaces. Tailored to urban green space design, our framework comprises three steps: road system generation, region type planning, and model placement. First, it constructs undirected graphs to generate a sound road system for an empty site and divides the space into separate regions. Then it applies a genetic algorithm to plan suitable surface and vegetation for every region. Finally, it places landscape models based on various patterns and adds embellishments to complete an appealing urban green space. Our framework enables the automatic production of urban green spaces. Through extensive experiments, we demonstrate that the generated results are plausible and reasonable.

As the virtual reality (VR) technology strives to provide immersive and natural user experiences, the challenge of aligning vast virtual environments with limited physical spaces remains significant. This survey comprehensively explores the advancements in redirected walking (RDW) techniques aimed at overcoming spatial constraints in VR. RDW addresses this by subtly manipulating users’ physical movements to allow for seamless navigation within constrained areas. The survey delves into gain perception mechanisms, detailing how slight discrepancies between virtual and real-world movements can be utilized without user awareness, thus extending the effective navigable space. Various RDW control algorithms for gain-based RDW are analyzed, highlighting their implementation and effectiveness in maintaining immersion and minimizing perceptual disturbances. Furthermore, novel methods extending beyond traditional gain-based techniques are discussed, showcasing innovative approaches that further refine VR interactions. The practical implications of RDW in enhancing safety and reducing physical collisions in VR environments are underscored, alongside its potential to improve user experience by aligning virtual exploration more closely with natural human behavior patterns. Through a thorough review of existing literature and recent advancements, this survey provides a systematic understanding for researchers, developers, and industry professionals. It underscores the importance of RDW in the future of VR, emphasizing RDW's role in making VR more accessible and practical across various applications, from education and training to therapy and entertainment. The paper concludes with a forward-looking perspective on the continued evolution and potential of RDW in revolutionizing virtual reality experiences.