Multi-Robot Cell Coordination With Dynamic Task Reallocation
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Solution Overview
Problem
Multi-robot cells in production systems face challenges with manual programming, error-prone task distribution, and increased downtime due to robot malfunctions, leading to reduced productivity and increased costs.
Innovation Solution
An automated method for coordinating robot activities in a multi-robot cell, which detects scheduled tasks with dependencies, assigns tasks to individual robots, transmits instructions, records the robot cell state, and optimizes task execution to minimize downtime and maximize productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual programming is used to distribute tasks among robots, then task distribution can be customized, but the process becomes error-prone and time-consuming
Solution Approach 1:
The system enables robots to autonomously monitor their own operational status and automatically request task reallocation when malfunctions occur, eliminating the need for manual intervention in task distribution adjustments and reducing programming errors
Solution Approach 2:
Manual programming is replaced by an automated digital coordination system that uses sensors, communication interfaces, and control algorithms to dynamically allocate tasks among robots based on real-time operational status
2Reliability
If a robot malfunction occurs in a multi-robot cell, then the fault must be rectified before other robots can continue, but this leads to extended production standstill and reduced productivity
Solution Approach 1:
The task distribution system dynamically adapts to changing operational conditions by automatically reallocating tasks from malfunctioning robots to operational robots in real-time, maintaining system continuity without fixed static task assignments
Solution Approach 2:
The system changes the operational parameters of task allocation by transitioning from a static pre-programmed distribution to a dynamic distribution based on real-time robot status, enabling continuous production during malfunctions
3Adaptability or versatility
If the number of robots in a multi-robot cell is increased to handle complex tasks, then task capability is enhanced, but the probability of malfunction increases
Solution Approach 1:
The coordination system creates a universal task management framework that can handle various task types and robot configurations, allowing any operational robot to perform any assigned task through dynamic reallocation rather than dedicated fixed assignments
4Productivity
If automated task reallocation is implemented during operation, then downtime is reduced, but system complexity increases
Solution Approach 1:
A central coordination server acts as an intermediary between robots, managing the complexity of task reallocation logic centrally while keeping individual robot controllers simple, facilitating automated downtime reduction without overwhelming individual components
Data Source
AI summary
A method for automated coordination of the activities of a plurality of robots that perform activities as a group in a common robot cell, scheduled tasks of the robots of the common robot cell are detected, with dependencies existing among the tasks. The scheduled tasks are assigned to individual robots of the common robot cell during the operation of the common robot cell. Instructions for the execution of the scheduled tasks are transmitted to the individual robots of the common robot cell. During the execution of the tasks, the robot cell state is recorded. The execution of the tasks not yet is optimised during the operation of the common robot cell, taking into account the current robot cell state and the dependencies existing among the tasks.