Autonomous Processing Robot Control Using Color and Chlorophyll Sensing
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Solution Overview
Problem
Existing autonomous mobile processing robots lack efficient methods for determining the appropriate control type based on environmental factors like color, chlorophyll content, and temperature, leading to suboptimal handling and processing of objects in green areas.
Innovation Solution
A method involving color, chlorophyll, and temperature measurement principles to autonomously detect and determine the control type for an autonomous mobile processing robot, enabling improved handling and processing by linking or fusing detected information to select the appropriate control mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only color measurement is used to determine control mode, then device complexity is reduced, but measurement precision and reliability of object identification deteriorate
Solution Approach 1:
The patent combines color measurement and chlorophyll measurement into a unified measurement system. The processing robot is equipped with both a color sensor and a chlorophyll sensor that work together to capture complementary information about the object, thereby improving identification accuracy without significantly increasing system complexity.
Solution Approach 2:
The measurement system is designed to perform multiple functions: it can detect both color properties and chlorophyll content using the same robotic platform and processing unit. This multi-functionality allows the system to gather comprehensive object characteristics while maintaining cost-effectiveness and operational simplicity.
2Measurement precision
If multiple measurement principles (color and chlorophyll) are used independently, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent integrates color measurement and chlorophyll measurement into a single coordinated system. Both measurement principles are applied simultaneously by the same processing robot, and their results are combined to determine the control mode, achieving high precision without requiring separate independent systems.
Solution Approach 2:
The processing robot autonomously performs both color and chlorophyll measurements and independently determines the control mode based on the combined information. This self-service capability eliminates the need for complex external control systems while maintaining high measurement precision.
3Ease of operation
If autonomous processing is implemented, then ease of operation improves, but reliability of processing may deteriorate due to lack of human oversight
Solution Approach 1:
The system continuously measures color and chlorophyll information and uses this feedback to dynamically determine and adjust the control mode. This closed-loop feedback mechanism ensures that the autonomous robot can reliably adapt to different objects and conditions, maintaining high processing reliability without human intervention.
Solution Approach 2:
The processing robot independently performs measurement, analysis, and processing operations without requiring human control or oversight. The system uses its own sensor data to make autonomous decisions about processing parameters and control modes, achieving both ease of operation and reliability through self-sufficient operation.
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
Enables cost-effective, automatic, and improved handling of objects by determining the optimal control type based on detected environmental factors, enhancing the robot's ability to process surfaces independently and efficiently.
Implementation Method 1
Acquiring color information, in particular the content of the color information, about a color, in particular a value of the color and/or the color, of an object using a color measurement principle
Implementation Method 2
Acquiring chlorophyll information, in particular the content of the chlorophyll information, about a chlorophyll content, in particular a value of the chlorophyll content and/or the chlorophyll content, of the object using a chlorophyll measurement principle
Data Source
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AI summary
The invention relates to a method for operating an autonomous mobile processing robot (1), wherein the method comprises the steps: a) acquiring color information (FI) about a color (Fa, Fb) of an object (100a, 100b) using a color measurement principle (FM) and acquiring chlorophyll information (CI) about a chlorophyll content (Ca, Cb) of the object (100a, 100b) using a chlorophyll measurement principle (CM) independently of the color measurement principle (FM), b) determining a control mode (STa, STb) from a set of different control modes (STa, STb) of the processing robot (1) based on at least the acquired color information (FI) and the acquired chlorophyll information (CI), and c) controlling the processing robot (1) in the determined control mode (STa, STb).