Robot Motion Planning With Image-Based Repository Detection
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Solution Overview
Problem
Existing robotic systems face challenges in accurately and efficiently transferring objects between repositories due to variations in repository structures and object poses, which affects the reliability and speed of robotic trajectory planning.
Innovation Solution
A computing system that communicates with a robot equipped with a camera and end effector, performing a series of commands to approach, detect, and transfer objects between repositories, using a combination of pre-planned and image-assisted trajectories to enhance accuracy and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional robotic systems use fixed trajectory planning for object transfer, then the system structure is simple and easy to implement, but the system cannot adapt to variations in repository structures and object poses, resulting in low reliability
Solution Approach 1:
The system dynamically adjusts the robot trajectory based on real-time image analysis of repository structures and object poses. Instead of using fixed pre-programmed paths, the trajectory planning adapts to actual conditions observed by the camera system, allowing the robot to handle variations in repository configurations and object positions while maintaining reliable object transfer operations
Solution Approach 2:
The system incorporates image-based feedback from camera sensors to continuously monitor and adjust the robot trajectory. The image analysis provides real-time information about repository structures and object poses, which feeds back into the trajectory planning algorithm to optimize the transfer path, thereby improving reliability without requiring overly complex manual programming
2Productivity
If the system performs comprehensive image analysis and adaptive trajectory planning, then the speed and accuracy of object transfer improve, but the computational processing time increases
Solution Approach 1:
The system performs preliminary image capture and analysis before the robot executes the transfer motion. By capturing images early in the process and analyzing repository structures and object poses in advance, the system prepares trajectory data beforehand, allowing the actual object transfer to proceed quickly without real-time computational delays during the critical transfer phase
Solution Approach 2:
The trajectory planning process is segmented into distinct phases: image capture phase, image analysis phase, trajectory computation phase, and execution phase. This segmentation allows computational intensive tasks to be performed in parallel with robot motion where possible, and separates planning from execution to optimize both accuracy and speed without requiring all computations to complete before transfer begins
3Measurement precision
If the robot uses a camera for real-time image analysis, then the accuracy of detecting repository structures and object poses improves, but the system complexity and cost increase
Solution Approach 1:
The system uses image processing algorithms as an intermediary between the camera sensor and the robot control system. Rather than requiring complex direct sensing of repository structures and object poses, the camera captures visual information that is then processed through image analysis algorithms to extract relevant geometric and positional data, which subsequently guides the robot trajectory. This intermediary processing layer simplifies the overall system architecture while maintaining high measurement precision
Data Source
AI summary
A method and computing system for transferring objects between a source repository and a destination repository is provided. The computing system is configured to operate by a combination of pre-planned and image base trajectories to improve speed and reliability of object transfer. The computing system is configured to capture image information of repositories and use the captured information to alter or adjust pre-planned trajectories to improve performance.