This research develops an effective and precise collision detection (CD) algorithm for real-time simulation in virtual environments such as computer graphics, realistic and immersive virtual reality (VR), augmented reality (AR) and physical-based simulation within an enhanced algorithm for object collision detection in 3D geometry. We describe an improved algorithm through a comparison in the application of a central processing unit (CPU) and graphics processing units (GPU). Although leveraging CPU for computational speed improvements has gained significant recognition in recent years, this study distinguishes by tracking 3D geometry bounding volume hierarchy (BVH) constructed in a spatial decomposition structure with a focus on Octree-based Axis-Aligned Bounding Box (AABB) structure in 3D scene to compute collision detection to swiftly reject disjoint objects and minimize the number of triangle primitives that need to be processed and then the Möller method is utilized to compute precise triangle primitives, further enhancing the efficiency and precision of the collision detection process. This approach is also designed to implement computation with GPU which utilizes the high-level shader language (HLSL) programming language on the compute shader Unity3D. AABB is structured as the maximum and minimum hexahedron enclosing an object that is parallel to the coordinate axis. Otherwise, GPU computational technique is a crucial method for further enhancing the object's performance. The proposed method utilizes Octree AABB-based GPU parallel processing to reduce the computational load of real-time collision detection simulations and to handle multiple computations simultaneously. Comparative performance evaluations demonstrate that our GPU-accelerated framework consistently reaches the fastest collision detection times from 1.01 to 45.62 times, respectively.

Real-time physics simulations are vital for creating immersive and interactive experiences in extended reality (XR) applications. Balancing computational efficiency and simulation accuracy is challenging, especially in environments with multiple deformable objects that require complex interactions. In this study, we introduce a GPU-based parallel processing framework combined with a position-based dynamics (PBD) solver to tackle these challenges. The system is deployed within the Unity engine and enhances real-time performance through the use of sophisticated collision detection and response algorithms. Our method employs an AABB-based bounding volume hierarchy (BVH) structure to efficiently detect collisions, and incorporates the Möller–Trumbore algorithm for precise triangle-level interactions. We also boost computational efficiency by storing collision data in GPU-accessible 2D textures. Experimental assessments show performance improvements of up to 1705% in GPU simulations over CPU counterparts, achieving stable real-time frame rates for complex models such as the Stanford Bunny and Armadillo. Furthermore, utilizing 2D texture storage improves the FPS by up to 117%, confirming its efficacy for XR applications. This study offers a robust, scalable framework for real-time physics simulations, facilitating more natural and immersive XR experiences.

Performing accurate and precise collision detection is a key to real-time applications in computer graphics, games, physical-based simulation, virtual reality, augmented reality, and research and development. Researchers have developed numerous methods to minimize computation time and enhance the accuracy of collision detection for pair-object collisions. Although the performance of the central processing unit (CPU) has significantly improved in recent years, it is still insufficient for many applications. In this study, we have developed an improved algorithm for geometric bounding volume hierarchy (BHV) in 3D spatial subdivisions using an Octree-based axis-aligned bounding box (AABB) structure. The AABB structure is used for collision detection and its computation by the central processing unit and graphic processing unit (GPU), which is implemented on the compute shader in Unity3D. AABB was defined as the maximum and minimum hexahedron within an object that is parallel to the coordinate axis. While GPU computing is essential for enhancing the object’s performance. The proposed algorithm approaches Octree AABB-based GPU parallel processing to reduce the calculation or process of simulation for real-time collision detection and handles multiple computations. In the CPU environment, the algorithm spent 2.9 fps when simulating up to 20 objects of the Torus Model that contains 2.3 K vertices and 4.6 K triangles. In the GPU environment, it spent 635.62 fps with 20 objects, and the maximum number increased to 180 objects in real-time.