Multi-Robot Singulation Coordination for Conflict-Free Throughput
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Solution Overview
Problem
Manual singulation of items in parcel and distribution centers is labor-intensive and inefficient, and the use of robots is challenging due to the cluttered mix of items and dynamic flow, making it difficult to identify, grasp, and separate items in an automated manner.
Innovation Solution
A robotic singulation system using a robotic arm with a suction-based end effector, coordinated by a control computer with vision systems and sensors, to pick and place items on a segmented conveyor, with the ability to invoke human assistance when needed, and coordinate multiple robots to maximize throughput and avoid conflicts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual singulation is used, then items can be separated, but labor intensity is high and throughput is low
Solution Approach 1:
The system uses vision systems and automated robotic arms to perform singulation independently without human intervention. The robotic arm automatically identifies, grasps, and places items based on vision system detection, enabling the system to serve itself and eliminate manual labor while maintaining high throughput.
Solution Approach 2:
The patent replaces manual mechanical operations with an automated robotic system comprising a robotic arm, vision systems, and control computers. This substitution eliminates human labor while achieving automated singulation at high speed, directly resolving the contradiction between productivity and automation extent.
2Extent of automation
If robotic singulation is implemented, then automation increases, but difficulty in identifying and grasping items in cluttered environments increases
Solution Approach 1:
The vision system acts as an intermediary between the robotic arm and the cluttered items. It processes images to identify item locations, orientations, and characteristics, translating complex visual information into actionable data for the robotic arm. This intermediary layer simplifies the detection and grasping tasks despite cluttered environments.
Solution Approach 2:
The system performs preliminary actions by using the vision system to detect and plan grasping sequences before the robotic arm executes movements. The vision system pre-identifies target items and calculates optimal grasping points, allowing the robotic arm to efficiently navigate cluttered environments without real-time decision-making delays.
3Productivity
If multiple robots are coordinated, then throughput increases, but risk of conflict and collision increases
Solution Approach 1:
The control computer continuously monitors the positions and movements of multiple robotic arms through vision systems and sensors. This real-time feedback allows the system to detect potential conflicts or collisions between robots and dynamically adjust their trajectories and speeds, maintaining high throughput while ensuring safe operation.
Solution Approach 2:
The system employs dynamic coordination where robotic arms can adjust their motion paths and speeds in real-time based on the actions of other robots. This dynamic adaptation allows multiple robots to operate in close proximity without conflicts, maximizing collective throughput while maintaining reliability through continuous motion planning adjustments.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves efficient and automated singulation of items, improving collective throughput and reducing labor intensity by accurately identifying and separating items, even in a cluttered environment, and adapting to handle items of varying sizes and orientations.
Implementation Method 1
a robotic arm with a suction-based end effector
Data Source
AI summary
A robotic singulation system is disclosed. In various embodiments, sensor data including image data associated with a workspace is received. The sensor data is used to generate a three dimensional view of at least a portion of the workspace, the three dimensional view including boundaries of a plurality of items present in the workspace. A grasp strategy is determined for each of at least a subset of items, and for each grasp strategy a corresponding probability of grasp success is computed. The grasp strategies and corresponding probabilities of grasp success are used to determine and implement a plan to autonomously operate a robotic structure to pick one or more items from the workplace and place each item singly in a corresponding location in a singulation conveyance structure.