Intelligent Navigation and Obstacle-Aware Fabrication for Mobile Additive Manufacturing Systems

2026-03-26

AI Summary

This work addresses the challenges faced by mobile additive manufacturing systems in dynamic environments, where obstacles and uneven terrain often compromise navigation stability, printing accuracy, and surface quality. To overcome these issues, the paper proposes a novel closed-loop control architecture that tightly integrates perception, mobility, and fabrication, enabling, for the first time, concurrent optimization of navigation and material deposition. Within a unified framework, the system synchronously ensures safe obstacle avoidance, high-precision motion, and stable printing through real-time sensor feedback, dynamic path planning, and adaptive process control. Both simulation and physical experiments demonstrate that the proposed approach effectively handles abrupt trajectory changes and external disturbances, significantly enhancing the autonomy, stability, and geometric fidelity of mobile additive manufacturing.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Multiagent Systems: Multiagent Planning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization

Abstract

As the demand for mass customization increases, manufacturing systems must become more flexible and adaptable to produce personalized products efficiently. Additive manufacturing (AM) enhances production adaptability by enabling on-demand fabrication of customized components directly from digital models, but its flexibility remains constrained by fixed equipment layouts. Integrating mobile robots addresses this limitation by allowing manufacturing resources to move and adapt to changing production requirements. Mobile AM Robots (MAMbots) combine AM with mobile robotics to produce and transport components within dynamic manufacturing environments. However, the dynamic manufacturing environments introduce challenges for MAMbots. Disturbances such as obstacles and uneven terrain can disrupt navigation stability, which in turn affects printing accuracy and surface quality. This work proposes a universal mobile printing-and-delivery platform that couples navigation and material deposition, addressing the limitations of earlier frameworks that treated these processes separately. A real-time control framework is developed to plan and control the robot's navigation, ensuring safe motion, obstacle avoidance, and path stability while maintaining print quality. The closed-loop integration of sensing, mobility, and manufacturing provides real-time feedback for motion and process control, enabling MAMbots to make autonomous decisions in dynamic environments. The framework is validated through simulations and real-world experiments that test its adaptability to trajectory variations and external disturbances. Coupled navigation and printing together enable MAMbots to plan safe, adaptive trajectories, improving flexibility and adaptability in manufacturing.

Problem

• mobile additive manufacturing
• navigation stability
• obstacle avoidance
• print quality
• dynamic environments

Innovation

• Mobile Additive Manufacturing
• Obstacle-Aware Navigation
• Closed-Loop Control
• Real-Time Process Integration
• Autonomous Manufacturing Robots