Common Communication Protocol for Inference System Object Recognition
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Solution Overview
Problem
Conventional object detection systems face challenges in recognizing objects with changes in location and orientation, and they often require significant training data and struggle with ambiguity in spatial features, leading to inadequate recognition of objects across different positions and orientations.
Innovation Solution
A common communication protocol (CCP) is introduced that includes pose information and object information, enabling inference systems to operate across diverse architectures and sensor modalities by converting sensory input into a standardized format, facilitating recognition and prediction of objects regardless of their location and orientation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional object detection models (CNN) are used to address changes in locations and orientations, then the system can recognize objects in varied positions, but the system requires significant amounts of training data
Solution Approach 1:
The patent transforms spatial information into explicit parameter representations (coordinates, orientations, distances) that are communicated through the protocol. This allows the system to handle location and orientation variations through parameter encoding rather than requiring extensive training data for each configuration
Solution Approach 2:
The patent introduces an intermediary communication protocol that translates sensory input into standardized pose and object information. This intermediary layer enables different sensor modalities and system architectures to communicate spatial relationships without requiring retraining, resolving the contradiction between adaptability and training data requirements
2Reliability
If conventional object detection systems are used, then the system can process sensory input, but the system struggles with ambiguity in spatial features leading to inadequate recognition
Solution Approach 1:
The patent segments spatial information into distinct components (pose information including location and orientation, and object information including identity and features). This segmentation reduces ambiguity by clearly separating spatial relationships from object characteristics, improving recognition reliability
Solution Approach 2:
The patent replaces conventional detection mechanisms with a standardized communication protocol that explicitly encodes spatial parameters. This substitution transforms ambiguous spatial feature detection into precise parameter communication, reducing recognition errors
3Adaptability or versatility
If inference systems use diverse architectures and sensor modalities, then the system can process various types of sensory input, but communication between components becomes complex
Solution Approach 1:
The patent creates a universal communication protocol that can handle multiple sensor modalities and system architectures through a single standardized interface. The protocol's ability to encode pose and object information in a format-independent manner enables diverse components to communicate without increasing complexity
Solution Approach 2:
The patent enforces homogeneous communication standards across all system components by requiring all pose and object information to follow the same protocol structure. This homogeneity simplifies inter-component communication while maintaining support for diverse sensor modalities and architectures
Data Source
AI summary
A common communication protocol (CCP) used across different components of an inference system that recognizes an object and its state, or affect changes in the state of the object to a targeted state, based on sensory input. One or more components may convert information they generate into a format compliant with the CCP for sending to one or more other components. The CCP includes pose information and object information of an object. The pose information indicates the location and the orientation of the object in a common coordinate system, as detected, inferred, predicted or targeted by a component of the inference system. The object information indicates either one or more features of the object, as detected, predicted or targeted, or identification of the object, as inferred or predicted by the component of the inference system.