Modular Robot Topology Recognition for Fast Reconfiguration
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Solution Overview
Problem
Existing modular reconfigurable robots face challenges in ease of use and efficiency due to complex mathematical modeling and programming requirements, making frequent reconfiguration impractical for non-expert users, especially in small and medium-sized enterprises, where task definitions vary frequently and maintenance intervals cause production line inefficiencies.
Innovation Solution
A modular configurable robot system with a master/slave software framework and custom electronic slave devices enables automatic on-the-fly robot topology recognition, kinematic and dynamic model generation, and controller tuning, facilitated by an electromechanical interface that automatically detects module orientation and retrieves necessary parameters from a centralized database, allowing for quick reconfiguration and operation without extensive user expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If modular reconfigurable robots are used to facilitate frequent task changes and maintenance, then adaptability and ease of repair are improved, but device complexity and difficulty of operation increase due to complex mathematical modeling and programming requirements
Solution Approach 1:
The system performs automatic topology recognition, model generation, and controller tuning without requiring user expertise in mathematical modeling or programming. The robot system itself carries out these complex tasks autonomously when modules are reconfigured, eliminating the need for users to manually perform complex setup procedures.
Solution Approach 2:
The system pre-generates robot models and controllers based on the detected module topology. By preparing these computational elements in advance automatically, the system eliminates the need for users to perform time-consuming mathematical modeling and programming tasks after reconfiguration.
2Ease of repair
If modular reconfigurable robots are used to enable selective maintenance of individual components, then ease of repair and productivity are improved, but loss of time increases due to manual model updating and controller reprogramming
Solution Approach 1:
When modules are replaced or reconfigured, the system automatically detects the new topology, generates updated robot models, and tunes controllers without requiring manual intervention. This self-service capability eliminates the time-consuming processes of manual model updating and controller reprogramming that would otherwise be necessary after maintenance activities.
3Productivity
If specialized non-modular robots are used to perform specific tasks efficiently, then productivity and reliability are improved, but adaptability decreases and purchasing multiple robots becomes economically infeasible
Solution Approach 1:
The modular robot system can be reconfigured to perform multiple different tasks by changing the combination and arrangement of standard modules. A single modular system replaces the need for multiple specialized robots, providing universal functionality across various applications while maintaining efficient task execution through automatic model generation and controller tuning.
4Manufacturing precision
If manual mathematical modeling and programming are used to program reconfigured robots, then manufacturing precision and control accuracy are maintained, but loss of time and difficulty of operation increase significantly
Solution Approach 1:
The system automatically generates accurate robot models and tunes controllers based on the detected module topology, eliminating the need for users to perform manual mathematical modeling. This self-service approach maintains control accuracy while reducing programming time from hours or days to minutes or seconds.
Solution Approach 2:
Manual mathematical modeling and programming tasks are replaced by an automated computational system that uses sensor data and module specifications to generate control models. This substitution transitions the process from manual intellectual labor to automated computational processing, maintaining accuracy while dramatically reducing time requirements.
Data Source
AI summary
A modular configurable robot, comprising robot modules comprising a coupling mechanism including an electrical coupling member comprising a network communication signal connection, an arrangement forming upon coupling an orientation signal, an integrated circuit comprising a microcontroller circuit with unique identification code and I/O ports coupled to said electrical coupling to receive orientation electrical signal, a communication slave module comprising ports and registers storing state values of the ports, one port pre-designated as input, the ports being open or closed depending on the port state, the robot comprising a master communication module forming with said slave modules a master slave communication network topology, a server hosting a database of robot module parameters, accessible by unique identification code, said master module retrieving from said communication slave module the unique identification code, and from the database robot module parameters, and from said microcontroller circuit said information of a relative orientation.