Robot Bin Picking With Reachability-Guided Object Orientation
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Solution Overview
Problem
Existing robotic systems face challenges in efficiently picking and orienting objects from a bin due to variations in size, shape, and orientation, leading to reduced throughput and increased operator intervention.
Innovation Solution
A method involving a robotic system that captures background and component images, evaluates reachability, and uses a combination of image processing and mechanical manipulation (such as stirring or agitating) to determine and achieve optimal picking and orientation of objects, ensuring successful picking and placement on a conveyor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robot attempts to pick objects directly from a bin with varied orientations, then the picking complexity increases, but the throughput decreases and operator intervention increases
Solution Approach 1:
The system performs preliminary actions by capturing images of objects in the bin before picking, determining reachability of pre-pick targets, and evaluating whether objects can be successfully picked. This preliminary evaluation allows the system to plan the picking sequence and avoid failed pick attempts, thereby increasing throughput while managing complexity through intelligent preprocessing.
2Reliability
If the robot uses a fixed picking approach without reachability evaluation, then the operation is simpler, but the picking success rate decreases and operator intervention increases
Solution Approach 1:
The system implements feedback by capturing images of the bin contents, evaluating reachability of pre-pick and pick targets, and using this information to determine whether to attempt picking. This feedback loop ensures the robot only attempts picks that are determined to be successful, significantly improving picking success rate while the complexity is managed through automated image processing and evaluation algorithms.
3Speed
If the robot attempts to pick all objects regardless of reachability, then the operation is faster, but the number of failed picks increases reducing overall efficiency
Solution Approach 1:
The system performs preliminary reachability evaluation for both pre-pick targets and pick targets before attempting to pick objects. This preliminary action identifies which objects can be successfully picked and in what sequence, allowing the robot to maintain high picking speed by only attempting proven successful picks, thereby improving overall efficiency without sacrificing speed.
Data Source
AI summary
A method for operating a robot includes providing target data for a target object; determining whether a pre-pick target for the target object is reachable by the robot; determining whether a pick target is reachable by the robot; and executing a pick routine directing the robot to pick up the target object and deposit the target object at a desired location responsive to a determination that the pre-pick target and the pick target are reachable by the robot.