Cognitive Vision Controller for Multi-Camera Robot Configuration
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Solution Overview
Problem
Current cognitive robotics systems face challenges in optimizing robot vision capabilities, as they require efficient configuration of multiple cameras to respond to complex commands and dynamic environmental conditions, which affects their ability to interact with humans and perform tasks with the same accuracy and throughput as humans.
Innovation Solution
A cognitive vision controller program that integrates with a GUI-based interface and an IoT platform to configure a plurality of cameras, determining the appropriate camera types and configurations needed to respond to commands or conditions, optimizing robot vision systems by selecting and configuring cameras within a distributed data processing environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple cameras are configured to respond to complex commands, then the robot's visual intelligence and task performance accuracy are improved, but the system complexity and configuration difficulty increase
Solution Approach 1:
An automated camera configuration system acts as an intermediary between complex commands and multiple cameras. The system receives high-level commands, automatically determines optimal camera selections and configurations, and manages the coordination of multiple cameras without requiring manual configuration of each camera individually, thus resolving the contradiction between improved visual intelligence and increased system complexity
2Adaptability or versatility
If cameras are configured to respond to dynamic environmental conditions, then the robot's adaptability is improved, but the real-time processing requirements and system resource consumption increase
Solution Approach 1:
The system performs preliminary configuration of camera parameters and selections based on pre-defined environmental conditions and task requirements. By pre-configuring camera settings for various scenarios, the robot can quickly adapt to dynamic environmental conditions without requiring intensive real-time processing, thus resolving the contradiction between improved adaptability and increased resource consumption
Data Source
AI summary
In an approach to robot vision configuration, one or more computer processors receive a command for image capture by a robot. The one or more computer processors determine one or more cameras of a plurality of cameras to respond to the command. The one or more computer processors configure the one or more cameras to respond to the command.