Multi-Robot Load Balancing via Conveyor Encoder Synchronization
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Solution Overview
Problem
Existing pick and place robot systems with multiple robots on a conveyor face challenges in accurately establishing a common reference frame and load balancing, leading to inefficiencies and errors in part location and processing.
Innovation Solution
A system comprising multiple robots and controllers with integrated load re-balance, state change detection, communication, and motion control subsystems, allowing for workload adjustment, automated load migration, and conveyor encoder synchronization, enabling efficient load distribution and minimizing downtime due to faulty robots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple robots work on a conveyor with a common reference frame, then the system can perform pick and place operations, but the complexity of establishing and maintaining accurate track frames increases
Solution Approach 1:
The system uses the conveyor's own encoder as a reference source. Each robot controller independently calculates its track frame by measuring the encoder position when the robot is at a known reference location on the conveyor, eliminating the need for manual track frame teaching or external reference systems.
Solution Approach 2:
The system continuously monitors conveyor encoder positions and uses this feedback to dynamically adjust and maintain track frames. When conveyor position changes are detected, the system automatically updates the track frame calculations to maintain accuracy without manual intervention.
2Measurement precision
If the track frame is not set up accurately, then the robot cannot locate and pick up parts, but manual track frame setup is time-consuming and error-prone
Solution Approach 1:
The robot controller automatically determines its track frame by reading the conveyor encoder at a known reference position. This self-calibration process eliminates manual track frame teaching, reducing setup time and eliminating human error while achieving high precision through encoder-based measurement.
Solution Approach 2:
The system replaces manual mechanical track frame setup with an automated electronic calibration process using the conveyor encoder. The controller software automatically calculates track frame parameters based on encoder readings, substituting manual measurement and calculation with automated electronic determination.
3Reliability
If one robot fails or changes state, then the system downtime increases, but load balancing requires continuous monitoring and adjustment
Solution Approach 1:
The load re-balance subsystem continuously monitors the state of each robot and automatically detects when a robot fails or changes state. Based on this feedback, the system dynamically recalculates and redistributes the workload among remaining operational robots, maintaining system continuity without manual intervention.
Solution Approach 2:
The system implements dynamic load balancing where workload distribution is continuously adjusted based on real-time robot status. When robot states change, the load re-balance subsystem automatically recalculates optimal workload distribution and implements changes, allowing the system to adapt dynamically to failures or state changes.
4Measurement precision
If conveyor encoder synchronization is required across multiple robots, then positioning accuracy improves, but the complexity of encoder value communication and synchronization increases
Solution Approach 1:
The system merges the encoder reference function into a single centralized subsystem. One robot controller acts as the encoder reference source, and other robot controllers receive and synchronize to this single encoder signal. This consolidation eliminates the need for each robot to independently process encoder signals, reducing overall system complexity while maintaining synchronization accuracy.
Data Source
AI summary
A system for picking and packing applications is provided. The system includes a plurality of robots and a plurality of robot controllers. Each robot controller includes a load re-balance subsystem, a load balance subsystem, a robot state change detector subsystem, a communicator subsystem, and a motion control subsystem. Each of the robot controllers is interconnected and in communication with one another via the communicator subsystems. Each of the robots has a workload that may be selectively balanced. A method for balancing the workloads of the robots using built-in processors which run motion control is also provided.