Multi-Arm Fruit Picking Robot With Distributed Vision Positioning
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Solution Overview
Problem
Existing multi-arm picking robots suffer from significant deviations in fruit positioning due to the use of a single vision sensor mounted at a distance, leading to inefficient fruit picking operations.
Innovation Solution
A picking robot system with multiple first image collection modules mounted near each robotic arm and a second image collection module at the robot's base to determine the base coordinate system, processing fruit tree images to generate global fruit positioning distribution information, allowing precise control of robotic arms for collaborative operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single vision sensor is mounted at a distance from the operation surface, then the device complexity is reduced, but the measurement precision of fruit positioning deteriorates significantly
Solution Approach 1:
The patent divides the single vision sensor system into multiple distributed vision sensors, with each sensor positioned near a specific robotic arm. This segmentation allows each sensor to independently provide precise positioning data for fruits in its local field of view, eliminating the positioning deviation caused by long sensing distances while maintaining manageable system complexity through modular distribution.
Solution Approach 2:
The patent transitions from a single-point vision sensor to a distributed array of vision sensors positioned at multiple spatial locations and heights. This dimensional expansion creates a three-dimensional sensing network that provides both accurate local positioning and global spatial context, resolving the contradiction between simplicity and precision.
2Productivity
If multiple robotic arms are integrated for increased operation range, then the productivity is improved, but the device complexity and mutual interference between arms increase
Solution Approach 1:
The patent assigns dedicated vision sensors to each robotic arm, creating independent sensing channels that reduce mutual interference. Each arm has its own localized vision system for fruit detection and positioning, while the central controller coordinates overall task allocation. This segmentation enables parallel operation of multiple arms without significant coordination complexity.
Solution Approach 2:
The patent introduces a central controller as an intermediary that receives vision data from multiple distributed sensors and coordinates robotic arm movements. This intermediary layer abstracts the complexity of multi-arm coordination by processing spatial relationships and task assignments centrally, allowing each arm to operate semi-independently while maintaining overall system coherence.
3Measurement precision
If vision sensors are positioned close to robotic arms, then the measurement precision of fruit positioning is improved, but the device complexity increases due to multiple sensors
Solution Approach 1:
The patent implements a one-to-one mapping between robotic arms and vision sensors, where each arm has a dedicated sensor positioned close to it. This segmentation strategy achieves high positioning precision for each arm's operational zone while keeping the overall system architecture simple and modular, avoiding the complexity of a single centralized sensor system.
Data Source
AI summary
A picking robot, a fruit positioning method and apparatus therefor, an electronic device, and a medium are provided. The robot includes a robot body including a processor and a plurality of robotic arms. A plurality of first image collection modules and one second image collection module are mounted on the robot body. Each robotic arm has one corresponding first image collection module mounted nearby. Each first image collection module does not interfere with the corresponding robotic arm. The second image collection module is mounted at a position of a base of the robot body. The processor is configured to determine, based on fruit tree images of respective sub-areas in an operation area that are collected by respective first image collection modules and the base coordinate system, global fruit positioning distribution information of the operation area, and control the robotic arms to perform collaborative operation.