Robotic Sortation Using Multi-Modal Object Recognition and Grasp Selection
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Solution Overview
Problem
Current sorting systems rely heavily on human intervention and are inefficient in automatically identifying and sorting a variety of objects in dynamic, heterogeneous environments, as they struggle to handle objects with obscured or non-visible barcodes and require manual assistance for optimal grasp selection.
Innovation Solution
A robotic sortation system that employs automated scanners and a robotic arm with perception units, including cameras and depth sensors, to identify objects, determine optimal grasp locations, and plan motion for efficient sorting, allowing human assistance for learning and improving grasp strategies, and utilizing a central computing system for determining destination locations based on object identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated scanning is used to identify objects, then productivity is improved, but measurement precision deteriorates when barcodes are obscured or non-visible
Solution Approach 1:
The system changes the identification parameter from barcode-only recognition to multi-parameter recognition including visual features, depth information, and geometric properties. This allows objects to be identified even when barcodes are obscured, maintaining high productivity while improving measurement precision through alternative identification parameters.
Solution Approach 2:
The patent introduces perception units (cameras, depth sensors) as intermediaries between the scanning system and objects. These intermediaries capture additional information about objects, enabling identification through multiple modalities when barcodes are not visible, thus resolving the contradiction between automated scanning speed and identification accuracy.
2Measurement precision
If human operators manually sort objects, then measurement precision is maintained through visual inspection, but productivity decreases due to manual processing
Solution Approach 1:
The patent replaces the mechanical human sorting system with an automated robotic system equipped with perception units and depth sensors. This substitution maintains measurement precision through advanced sensing capabilities while dramatically improving productivity by eliminating manual processing bottlenecks.
Solution Approach 2:
The system enables objects to be automatically identified and sorted without human intervention by using perception units to capture object characteristics and the robotic arm to execute sorting actions. This self-service capability maintains accuracy while achieving high-speed automated processing.
3Productivity
If a robotic arm is used to grasp objects, then productivity is improved through automation, but reliability deteriorates due to difficulty in selecting optimal grasp locations
Solution Approach 1:
The patent performs preliminary analysis of object geometry and surface properties using depth sensors and perception units before the robotic arm attempts grasping. This preliminary action identifies optimal grasp locations and approaches, ensuring high reliability while maintaining automated productivity.
Solution Approach 2:
The system incorporates feedback mechanisms where perception units continuously monitor object positions and orientations, and the system adjusts grasp planning based on this feedback. This closed-loop control improves grasp success rates while maintaining high-speed automated operation.
4Measurement precision
If multiple sensors and perception units are added to improve object identification, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent designs perception units that serve multiple functions: cameras capture visual information for identification, depth sensors provide geometric data for grasp planning, and the same system supports both identification and sorting operations. This multi-functionality reduces overall system complexity while maintaining high measurement precision.
Data Source
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AI summary
A sortation system is disclosed for providing processing of homogenous and non-homogenous objects in both structured and cluttered environments. The sortation system includes a programmable motion device including an end effector, a perception system for recognizing any of the identity, location, and orientation of an object presented in a plurality of objects, a grasp selection system for selecting a grasp location on the object, the grasp location being chosen to provide a secure grasp of the object by the end effector to permit the object to be moved from the plurality of objects to one of a plurality of destination locations, and a motion planning system for providing a motion path for the transport of the object when grasped by the end effector from the plurality of objects to the one of the plurality of destination locations, wherein the motion path is chosen to provide a path from the plurality of objects to the one of the plurality of destination locations.