Distributed Multi-Robot System Architecture
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Solution Overview
Problem
Traditional consumer service robots are costly and functionally restricted due to their self-contained architecture, which limits their adaptability and interaction capabilities, making them singular in purpose and lacking real-time adaptability beyond basic object detection and avoidance.
Innovation Solution
A distributed multi-robot system architecture where a robot manager with wireless communication modules coordinates and facilitates communication among multiple robots, enabling shared resources, mapping, navigation, and software updates, allowing for more efficient and adaptable service functions across various environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a self-contained architecture with all physical actuators, perception, and computation systems is used in each robot, then each robot can operate autonomously, but the cost and device complexity increase significantly
Solution Approach 1:
The system divides functionality between mobile robots and a stationary base unit. The base unit houses complex computation systems, perception processing, and resource management, while robots contain only essential actuators and communication modules. This segmentation allows robots to operate autonomously in mobility tasks while reducing on-board complexity.
Solution Approach 2:
A wireless communication system acts as an intermediary between the base unit and multiple robots. The base unit serves as a central resource pool that dynamically allocates computational tasks, perception data, and control commands to appropriate robots, enabling autonomous operation without requiring full self-containment in each robot.
2Adaptability or versatility
If multiple functions are integrated into a single robot, then the robot can perform diverse tasks, but the cost increases significantly
Solution Approach 1:
The base unit is designed as a universal resource pool that can support multiple different robot types simultaneously. Different robot configurations (cleaning robots, delivery robots, inspection robots) can access shared resources including computation power, perception algorithms, and facility maps, enabling diverse service tasks without duplicating expensive components in each robot.
3Adaptability or versatility
If each robot has full computation and perception systems, then the robot can adapt to different environments, but energy consumption increases
Solution Approach 1:
Complex computation systems, perception processing units, and large-scale environmental models are extracted from mobile robots and relocated to the stationary base unit. Robots retain only minimal on-board processing for immediate sensorimotor control, while sophisticated adaptation tasks are offloaded to the base unit's powerful computation systems, dramatically reducing on-board energy consumption.
4Device complexity
If a centralized architecture with all functions in one robot is used, then the system is simpler to manage, but the robot cannot serve multiple facility environments effectively
Solution Approach 1:
The system architecture is made dynamic through wireless communication that enables flexible task allocation and resource distribution. The base unit can dynamically assign different environments and tasks to different robots based on their capabilities and current conditions, allowing the system to adapt to multiple facility environments while maintaining centralized management through the base unit's control software.
Data Source
AI summary
A system is provided that includes at least one manager and one or more robots configured to communicate wirelessly. The manager can include certain functions that generate data, instructions, or both used by one or more robots. The manager can also facilitate communications among several robots, or robots could also be configured to communicate directly.