End Effector Grip Width Estimation Using Depth Data
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Solution Overview
Problem
Current systems fail to accurately estimate the opening width and holding position of an end effector for grasping objects with arbitrary widths, leading to potential collisions and inefficient object handling.
Innovation Solution
A holding parameter estimation device and method that acquire information about the end effector, object, and depth data to estimate the opening width and holding position using an end effector model, depth data, and rule maps, ensuring optimal grip configuration and avoiding collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the opening width of the end effector is not accurately estimated, then the object handling efficiency is reduced and collisions may occur, but increasing the estimation accuracy requires more complex calculation processes
Solution Approach 1:
The system pre-acquires information about the end effector structure and creates depth maps of the environment before performing opening width estimation. By preparing these data structures in advance, the actual estimation process can proceed more efficiently without requiring complex real-time calculations, thus resolving the contradiction between accuracy and computational complexity
Solution Approach 2:
The patent introduces an intermediary calculation process that uses depth map data and pre-acquired end effector information as intermediate representations. Instead of directly calculating opening width from raw sensor data, the system uses these intermediate structures to simplify the estimation process while maintaining accuracy, effectively mediating between complex raw data and the final estimation result
2Measurement precision
If the holding position is not accurately determined, then object handling efficiency decreases and collisions may occur, but accurate determination requires sophisticated algorithms
Solution Approach 1:
The system performs preliminary acquisition of depth map data and end effector information before holding position estimation. By preparing these data structures in advance and organizing them in a suitable format, the actual position estimation can be performed using simpler algorithms rather than sophisticated real-time processing, thus reducing algorithmic complexity while maintaining accuracy
Solution Approach 2:
The patent creates a virtual model (copy) of the end effector and its environment using depth map data. This virtual copy allows the system to perform position estimation in the virtual model space rather than directly in physical space, simplifying the algorithm requirements while achieving accurate holding position determination
3Reliability
If the end effector model is not used, then the calculation process is simpler, but the estimation accuracy and reliability decrease
Solution Approach 1:
The patent creates a virtual copy (model) of the end effector that includes its geometric and physical properties. This model is used to simulate and predict the end effector's behavior and interactions with objects, significantly improving estimation reliability. The model acts as a simplified representation that captures essential characteristics without requiring full physical complexity
Data Source
AI summary
A holding parameter estimation device includes an interface and a controller. The interface acquires information concerning an end effector, holding target information, and depth data. The controller acquires an end effector model based on the information. The controller estimates an opening width of a holder for holding of a holding object by the holder based on the end effector model, the holding target information, and the depth data.