Robotic AM Control Architecture for Multi-Robot Coordination

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Solution Overview

Problem

Existing additive manufacturing systems face challenges in coordinating operations across multiple robots and components from different vendors, managing complex communication latencies, and handling dynamic changes in a non-static system environment, leading to inefficiencies and potential collisions.

Innovation Solution

A control architecture that integrates planning and control nodes, perception nodes, and simulation modules to provide real-time and non-real-time instructions, enabling coordinated movement and dynamic adjustments across heterogeneous robotic systems, with centralized error detection and direct control of component parameters.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If multiple robots from different vendors are integrated into a single additive manufacturing system, then the system's productivity and manufacturing capability are improved, but the device complexity and coordination difficulty increase significantly

Engineering Contradiction:

Improvemanufacturing capabilityVSAvoidsystem coordination complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The control system is divided into separate planning nodes and control nodes. Planning nodes handle high-level task coordination while control nodes manage real-time robot execution. This segmentation allows independent development and optimization of each node type while reducing overall system complexity through modular architecture.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

A standardized communication protocol acts as an intermediary between robots from different vendors. The protocol includes standardized message formats, data types, and communication interfaces that enable heterogeneous robots to interact seamlessly without requiring vendor-specific integration code.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If real-time control adjustments are implemented to handle dynamic changes, then the system's adaptability is improved, but communication latencies and control complexity increase

Engineering Contradiction:

Improvedynamic adaptabilityVSAvoidcommunication latency

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-calculating robot trajectories and preparing control commands in advance. The planning nodes generate detailed motion plans before execution, allowing the real-time control nodes to focus only on executing pre-planned paths rather than making complex decisions during execution, thereby reducing communication latency.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The control architecture dynamically adjusts the level of autonomy based on system state. During normal operation, robots execute pre-planned paths with minimal communication. When dynamic changes are detected, the system transitions to higher-level control interventions, optimizing the balance between real-time responsiveness and communication efficiency.

Inventive Principle:

Principle #15Dynamics

3Reliability

If centralized control is implemented to coordinate multiple robots, then the system's reliability is improved through centralized error detection, but the device complexity and control burden increase

Engineering Contradiction:

Improveerror detection capabilityVSAvoidcontrol architecture complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The centralized control function is segmented into distributed control nodes, each responsible for specific robots or task groups. Each control node independently monitors its assigned robots and detects errors locally, then reports to central planning nodes. This segmentation maintains comprehensive monitoring capability while distributing computational burden and reducing single-point complexity.

Inventive Principle:

Principle #1Segmentation

4Adaptability or versatility

If heterogeneous robots from different vendors are used, then the system's adaptability is improved, but the difficulty of detecting and measuring system state increases

Engineering Contradiction:

Improvevendor independenceVSAvoidsystem state measurement

Core Design Contradiction:

Adaptability or versatilityVSDifficulty of detecting and measuring

Solution Approach 1:

The system standardizes the measurement and detection parameters across all heterogeneous robots by defining a unified parameter space. Each robot's state is represented using standardized data types and formats, transforming diverse vendor-specific parameters into a common representation that simplifies detection, measurement, and coordination across the entire fleet.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20260034739A1Control Architecture for Additive Manufacturing Robotic Systems

Publication Date: 2026.02.05 RELATIVITY SPACE INC

AI summary

Systems and methods for additive manufacturing robotic systems in accordance with embodiments of the invention are illustrated. One embodiment includes a method for visualizing a space. The method includes steps for receiving, at a set of one or more processors, a set of print data, wherein the set of print data comprises a first set of data for a first visualization, wherein the first set of data is received from a control system that controls a set of one or more robots for a print job to print a part, and a second set of data for a second visualization associated with the part, rendering, at the set of processors, the first and second visualizations based on the print data, wherein the first visualization includes a visualization of the print job, and displaying the rendered first and second visualizations.