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This summary is machine-generated.

This study introduces a systematic approach for collision-free robotic additive manufacturing (AM). It automates planning procedures, enabling autonomous construction of complex metal components.

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Area of Science:

  • Robotics and Manufacturing
  • Additive Manufacturing
  • Computational Geometry

Background:

  • Robotic additive manufacturing (AM) offers advantages in material deposition and orientation flexibility, reducing support structures and post-processing.
  • Current robotic AM relies on manual planning for feature identification, orientation, toolpath generation, and collision avoidance, hindering autonomy.
  • Multi-directional material accumulation poses collision risks between the nozzle and building geometry, limiting widespread adoption.

Purpose of the Study:

  • To develop a systematic and autonomous approach for robotic additive manufacturing (AM) that addresses collision-free planning.
  • To automate geometric reasoning, feature recognition, and trajectory generation for robotic AM processes.
  • To enable the fabrication of large, complex metal components not achievable with traditional AM methods.

Main Methods:

  • Integrated collision-avoidance conditions into the model decomposition step for robotic AM.
  • Associated decomposed volumes with constraints including accessibility, connectivity, and trajectory planning.
  • Generated a comprehensive workspace considering platform rotatability and additive features for collision-free sequencing.

Main Results:

  • Successfully automated planning procedures for robotic AM, ensuring collision-free operations.
  • Enabled association of decomposed geometric features with crucial manufacturing constraints.
  • Demonstrated a computationally effective method for building large and complex metal components autonomously.

Conclusions:

  • The proposed systematic approach significantly enhances the autonomy of robotic AM systems.
  • This method facilitates the creation of complex metal parts, overcoming limitations of traditional AM.
  • The approach lays the groundwork for integrating in situ monitoring and closed-loop control for improved build quality.