Auxiliary Sensor Support for Low-Confidence Robotic Picking
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Solution Overview
Problem
Automated robotic picking systems face inefficiencies due to reliance on vision components that may make decisions with low confidence or require human intervention, leading to delays and increased costs, especially when existing vision systems are not adequately integrated with intervention systems.
Innovation Solution
The implementation of observational support systems that can operate independently of existing vision systems, providing supplemental data and intervention assistance through auxiliary sensors and remote intervention systems to enhance robotic picking operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human intervention is used to address vision system limitations, then decision reliability is improved, but operational time is significantly delayed
Solution Approach 1:
An observational support system acts as an intermediary between the vision system and human operators. It receives data from the vision system, performs preliminary analysis and filtering, and only presents refined information to human operators when truly needed. This mediator role reduces the frequency and complexity of human intervention while maintaining decision reliability.
Solution Approach 2:
The observational support system performs preliminary analysis of vision system data before human operators are involved. It pre-processes sensor data, identifies potential issues, and prepares intervention recommendations in advance, so that when human operators do intervene, the required action can be executed immediately without delay.
2Extent of automation
If remote intervention system is integrated into existing vision system, then interventional capability is improved, but system complexity is significantly increased
Solution Approach 1:
The observational support system is designed as a separate, modular unit that can be independently deployed. It segments the intervention functionality from the core vision system, connecting through standardized interfaces. This segmentation allows the intervention capability to be added without complicating the existing vision system architecture.
Solution Approach 2:
The observational support system is designed to work with multiple types of vision systems and sensor configurations through universal interfaces. It can serve various picking applications and integrate with different robot platforms, providing multi-functional capability without requiring custom integration for each system, thereby reducing overall complexity.
3Productivity
If intervention system is pre-integrated into picking system, then operational efficiency is improved, but initial cost and setup complexity are increased
Solution Approach 1:
The observational support system is designed to be self-configuring and self-adapting to the specific picking environment. It automatically detects system parameters, configures appropriate analysis parameters, and adjusts its operation based on the deployed vision system characteristics. This self-service capability eliminates the need for expensive custom integration and extensive setup work.
Solution Approach 2:
The system is designed to dynamically adapt its level of intervention and analysis depth based on real-time operational needs. It can adjust its resource consumption and processing intensity according to the situation, providing high operational efficiency when needed while consuming minimal resources during normal operation, thereby justifying the investment through flexible performance.
4Reliability
If constant human monitoring is used for sensor systems, then detection reliability is improved, but time efficiency is significantly reduced
Solution Approach 1:
The observational support system implements intelligent feedback mechanisms that continuously monitor sensor data but only trigger alerts or require human attention when anomalies are detected. It uses automated analysis to filter normal variations from actual problems, providing feedback only when necessary. This maintains high detection reliability while avoiding the inefficiency of constant human monitoring.
Data Source
AI summary
The present disclosure is for systems and methods for providing observational support. The invention comprises an observational support system which generally operates as a supplemental system to an existing automated decision support system, such as a primary vision system for robotic picking operations. The observational support system provides an auxiliary sensor module which is operable to obtain data associated with a pick scene independently of the primary vision system and provide the data to an intervention system for further review and processing. The observational support system is generally called upon in situations where the primary vision system fails or encounters circumstances it cannot handle in a timely manner. The observational support system in combination with the intervention system provides supplemental assistance in these circumstances so that robotic picking operations can continue more readily.