Mushroom Picking Robot Suction Control and Dynamic Path Planning
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Solution Overview
Problem
Existing picking robots in mushroom cultivation face challenges in precise classification, quality detection, and volume gradation, leading to inefficiencies and high damage rates during the picking process.
Innovation Solution
A collaborative control method for a picking robot that involves dynamic path planning based on mushroom distribution and maturity, synchronized movement with a receiving mechanism, real-time image recognition for quality assessment, and intelligent grading and separation systems to optimize the picking and processing of mushrooms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual picking is used, then labor flexibility is maintained, but picking efficiency is low and labor consumption is high
Solution Approach 1:
The picking robot autonomously performs path planning, mushroom detection, picking, and conveying without continuous human intervention. The system self-adjusts based on real-time mushroom distribution data, achieving automated self-service operation that dramatically improves picking efficiency while reducing labor consumption.
Solution Approach 2:
The patent replaces manual mechanical picking with an automated robot system equipped with suction cups for gentle picking. The mechanical system is substituted with intelligent control algorithms that plan paths, detect mushrooms, and coordinate robot movements, transforming manual labor into automated intelligent operation.
2Measurement precision
If conventional picking robots are used, then automated picking is achieved, but classification precision and quality detection are insufficient
Solution Approach 1:
The system performs preliminary path planning based on pre-collected mushroom distribution data before actual picking begins. The robot pre-processes spatial information and maturity data to optimize its picking route, ensuring high-quality detection and classification are prepared in advance rather than reacting during picking.
Solution Approach 2:
The patent implements real-time feedback mechanisms where the robot continuously monitors mushroom quality, maturity, and position during picking. This feedback is fed back to the control system to dynamically adjust picking parameters, path planning, and classification criteria, thereby improving detection precision through iterative optimization.
3Productivity
If the receiving mechanism and picking robot operate independently, then operational simplicity is maintained, but synchronization coordination is poor causing efficiency decrease
Solution Approach 1:
The patent merges the picking robot and receiving mechanism into a coordinated unified system. Both components share common control algorithms for path planning and synchronization, allowing them to operate as an integrated team rather than independent units. This merging enables seamless coordination where the receiving mechanism is precisely positioned to catch mushrooms as they are picked.
Solution Approach 2:
The system dynamically adjusts the operation of both the picking robot and receiving mechanism based on real-time conditions. The receiving mechanism dynamically positions itself according to the robot's current location and picking rate, creating a flexible dynamic coordination system that adapts to varying workloads and maintains optimal efficiency throughout the picking process.
4Manufacturing precision
If simple mechanical grading is used, then device simplicity is maintained, but grading accuracy and volume gradation precision are insufficient
Solution Approach 1:
The patent replaces simple mechanical grading with intelligent image recognition and measurement systems. Cameras and sensors capture mushroom images, and algorithms automatically analyze size, shape, and quality parameters to determine grading categories. This substitution of mechanical grading with intelligent analysis dramatically improves grading accuracy and volume gradation precision.
Solution Approach 2:
The system changes the grading approach from purely mechanical size-based sorting to multi-parameter intelligent assessment. It considers mushroom diameter, height, shape regularity, color, and maturity stage simultaneously, using these multiple parameters to determine optimal grading categories. This parameter-based approach enables precise volume gradation and high-accuracy classification.
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
The method significantly improves picking efficiency, reduces mushroom damage, and enhances sorting precision, enabling continuous operation through seamless synchronization of the picking and receiving processes.
Implementation Method 1
picking, by a suction cup, the mushrooms
Data Source
AI summary
This application relates to a collaborative control method for a picking robot based on collaborative picking and collection of mushrooms, including the following steps: picking, by a suction cup, the mushrooms, and conveying, by a built-in conveying apparatus, the mushrooms to a discharge port; dynamically adjusting a movement path of the picking robot; synchronously moving a receiving mechanism and the picking robot, and ensuring the receiving mechanism to be aligned to the discharge port; separating, by a separating apparatus, mushrooms that meet a quality standard and unqualified mushrooms, where the mushrooms that meet a quality standard and the unqualified mushrooms respectively enter a first dropping hopper and a second dropping hopper; grading the mushrooms in the first dropping hopper for a second time, classifying the mushrooms based on volumes and diameters of the mushrooms; when any dropping hopper is to be fully loaded, triggering the receiving mechanism to alternately operate.