Self-tracked controller
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Solution Overview
Problem
Existing artificial-reality systems rely on external cameras and sensors to track handheld controllers, which can be occluded and require line of sight, leading to reduced functionality and increased complexity.
Innovation Solution
A self-tracking peripheral device equipped with internal cameras that capture images of its surroundings to determine its position in space without relying on external sensors or line of sight, using image processing to create a map and calculate its location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If external cameras and sensors are used to track handheld controllers, then tracking functionality is achieved, but occlusion occurs and line of sight is required
Solution Approach 1:
Instead of using external cameras to track the controller from outside, the patent inverts the approach by placing cameras on the controller itself to capture images of the environment. This self-tracking method eliminates occlusion issues because the controller tracks itself rather than being tracked by external devices that can be blocked by the user's hand or other objects.
Solution Approach 2:
The controller performs its own tracking function using onboard cameras and processing capabilities. The controller captures images, identifies features, and calculates its own position and orientation without requiring external tracking systems, making the system self-sufficient and immune to occlusion from external sources.
2Reliability
If external cameras and sensors are used to track handheld controllers, then tracking functionality is achieved, but system complexity increases
Solution Approach 1:
The patent extracts the tracking functionality from the external environment and embeds it within the controller itself. By moving the cameras, processors, and tracking algorithms into the controller, the system eliminates the need for complex external tracking infrastructure, reducing overall system complexity while maintaining reliable tracking.
Solution Approach 2:
The controller integrates multiple functions into a single device: it serves as both the input device and the tracking system. The onboard cameras serve dual purposes for both environmental mapping and self-tracking, reducing the need for separate external tracking components and simplifying the overall system architecture.
3Reliability
If multiple cameras are mounted on the controller for self-tracking, then occlusion risk is reduced, but device weight increases
Solution Approach 1:
The patent strategically positions cameras at specific locations on the controller where they can capture complementary views of the environment. By optimizing camera placement and using image processing algorithms, the system achieves reliable tracking with fewer cameras, thereby minimizing weight increase while maintaining tracking reliability across different hand positions and orientations.
Data Source
AI summary
The disclosed system may include a housing dimensioned to secure various components including at least one physical processor and various sensors. The system may also include a camera mounted to the housing, as well as physical memory with computer-executable instructions that, when executed by the physical processor, cause the physical processor to: acquire images of a surrounding environment using the camera mounted to the housing, identify features of the surrounding environment from the acquired images, generate a map using the features identified from the acquired images, access sensor data generated by the sensors, and determine a current pose of the system in the surrounding environment based on the features in the generated map and the accessed sensor data. Various other methods, apparatuses, and computer-readable media are also disclosed.