US20250173984
2025-05-29
Physics
G06T19/006
The patent application describes a system and method that leverages artificial intelligence (AI) to create assistive bots in extended reality (XR) environments. These bots, represented by computer-generated avatars, provide automated responses to user inquiries about both virtual and real-world objects. The technology aims to enhance user experience in XR settings by offering meaningful interactions and instructional support, particularly in educational contexts.
With advancements in immersive technologies like augmented reality (AR), virtual reality (VR), and mixed reality (MR), XR environments have become increasingly realistic and interactive. These environments offer unique opportunities for collaboration and information sharing that surpass physical world constraints. In educational settings, the presence of AI-driven assistive bots can mimic real-life interactions with teachers or tutors, thereby enriching the learning experience.
The invention focuses on improving the functionality of assistive bots in XR environments, such as those on platforms like Oculus/Meta Quest. These bots are designed not only to look like human instructors but can also take the form of animals, imaginary creatures, or even inanimate objects. They are capable of performing a variety of tasks, such as speaking, moving, and interacting with users to provide educational assistance.
The system can be implemented using a combination of hardware and software services. These services may reside on client devices or on servers within a content management system. The methods utilize computer-executable instructions stored on computer-readable media to perform functions necessary for the operation of assistive bots. This includes leveraging networked computing resources to execute complex processing tasks remotely.
An example XR device includes network interfaces for data communication, processors for executing software programs, and memory for storing data structures. The device also features input devices such as cameras and wearable sensors for tracking movements. The AI processes are implemented within the device's memory or network interfaces, enabling the assistive bots to learn from data patterns and improve their performance over time.