Multi-Sensor Robot Feedback Loop for Precise Enclosed-Space Detection
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Solution Overview
Problem
Existing systems lack the ability to accurately and efficiently perform operations within enclosed or dangerous spaces, such as cutting pipes, due to reliance on manual observation and lack of automated detection methods that can correlate disparate data sets.
Innovation Solution
The use of a robotic system equipped with multiple sensors, including cameras, infrared recognizers, LIDAR, and motion sensors, which fuse data to create a coherent 3D representation of the environment, enabling accurate mapping and operational control within these spaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used to detect features and defects in enclosed spaces, then measurement precision and detection accuracy are improved, but device complexity increases
Solution Approach 1:
The patent combines multiple sensors (visual camera, infrared camera, LIDAR, motion sensors) into a single integrated robotic system. The sensor fusion system merges data from all these sensors to create a unified coherent representation of the environment, improving detection accuracy while managing system complexity through integration.
Solution Approach 2:
The robotic system is designed with multi-functional sensors that can perform multiple detection tasks simultaneously. The same sensor suite used for mapping the environment also detects features, defects, and operational targets, eliminating the need for separate specialized devices and reducing overall system complexity.
2Productivity
If manual observation is used to detect features within the scanned environment, then device complexity is reduced, but productivity and detection efficiency deteriorate
Solution Approach 1:
The system employs automated detection algorithms that process sensor data without human intervention. The AI/ML models automatically identify features, defects, and operational targets from the sensor data, enabling the system to perform detection tasks autonomously and improving productivity while managing complexity through software-based solutions.
Solution Approach 2:
The patent replaces manual observation with automated sensor-based detection and AI/ML-based analysis. This substitution of mechanical/manual processes with electronic and computational systems dramatically improves detection efficiency and productivity, despite the increased technological complexity.
3Measurement precision
If automated detection methods are implemented to correlate disparate data sets, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces a sensor fusion system as an intermediary that processes and correlates data from multiple disparate sensors. This fusion system acts as a mediator that integrates visual, infrared, LIDAR, and motion data into a unified coherent representation, improving measurement precision while managing processing complexity through structured data integration.
Solution Approach 2:
The system transforms raw sensor data into standardized parameters and features that can be easily correlated and processed. By changing the parameter representation of data from multiple sensors into a unified format, the system improves correlation accuracy while reducing the complexity of data integration and processing.
4Manufacturing precision
If real-time sensor feedback is implemented for operational control, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent implements a feedback control system that uses real-time sensor data to adjust and control robotic operations. The sensor feedback provides continuous information about the environment and operational status, enabling precise control of cutting and other operations while managing control complexity through closed-loop control mechanisms.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for precise automated detection and operation within enclosed spaces, reducing errors and increasing efficiency by providing real-time data and control for tasks like pipe cutting.
Implementation Method 1
LIDAR to generate a 3D point cloud
Implementation Method 2
infrared cameras to detect temperature variations within the scanned environment
Data Source
AI summary
A method for assessing, by a robot, a feature of an environment based on data from one of the plurality of sensors, wherein the robot is positioned in the environment includes comparing, by the robot, the feature of the environment to an expected feature of the environment; creating, by the robot, a feedback loop based on the comparing step; and adjusting an operational condition of the robot based on the feedback loop.