Projector-Guided Non-Holonomic Mobile 3D Printing

Fused deposition modeling (FDM) using mobile robots instead of the gantry-based 3D printer enables additive manufacturing at a larger scale with higher speed. This introduces challenges including accurate localization, control of the printhead, and design of a stable mobile manipulator with low vibrations and proper degrees of freedom. We proposed and developed a low-cost non-holonomic mobile 3D printing system guided by a projector via learning-based visual servoing. It requires almost no manual calibration of the system parameters. Using a regular top-down projector without any expensive external localization device for pose feedback, this system enabled mobile robots to accurately follow pre-designed millimeter-level printing trajectories with speed control. We evaluate the system in terms of its trajectory accuracy and printing quality compared with original 3D designs. We further demonstrated the potential of this system using two such mobile robots to collaboratively print a 3D object with dimensions of 80 cm × 30 cm size, which exceeds the limitation of common desktop FDM 3D printers.

[1]  Xu Zhang,et al.  Large-scale 3D printing by a team of mobile robots , 2018, Automation in Construction.

[2]  Xinwu Liang,et al.  Image-Based Visual Servoing of a Quadrotor Using Virtual Camera Approach , 2017, IEEE/ASME Transactions on Mechatronics.

[3]  François Chaumette,et al.  Visual servo control. I. Basic approaches , 2006, IEEE Robotics & Automation Magazine.

[4]  Edwin Olson,et al.  AprilTag: A robust and flexible visual fiducial system , 2011, 2011 IEEE International Conference on Robotics and Automation.

[5]  Wojciech Zaremba,et al.  Domain randomization for transferring deep neural networks from simulation to the real world , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[6]  Xu Zhang,et al.  Printing-while-moving: a new paradigm for large-scale robotic 3D Printing , 2018, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[7]  Jianzhong Fu,et al.  Large-scale 3D printing technology based on the visual stitching method , 2019, Rapid Prototyping Journal.

[8]  Philippe Martinet,et al.  Position based visual servoing: keeping the object in the field of vision , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[9]  E. Malis,et al.  2 1/2 D Visual Servoing , 1999 .

[10]  Zhenghui Sha,et al.  A Generative Approach for Scheduling Multi-Robot Cooperative Three-Dimensional Printing , 2020, J. Comput. Inf. Sci. Eng..

[11]  Xu Zhang,et al.  Planning coordinated motions for tethered planar mobile robots , 2019, Robotics Auton. Syst..

[12]  Colin Bradley,et al.  Hierarchical Model Predictive Image-Based Visual Servoing of Underwater Vehicles With Adaptive Neural Network Dynamic Control , 2016, IEEE Transactions on Cybernetics.

[13]  Lee E. Weiss,et al.  Dynamic sensor-based control of robots with visual feedback , 1987, IEEE Journal on Robotics and Automation.

[14]  Wenchao Zhou,et al.  A Floor Power Module for Cooperative 3D Printing , 2017 .

[15]  Sergey Levine,et al.  Learning Visual Servoing with Deep Features and Fitted Q-Iteration , 2017, ICLR.

[16]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[17]  Davide Scaramuzza,et al.  A Tutorial on Quantitative Trajectory Evaluation for Visual(-Inertial) Odometry , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[18]  William J. Wilson,et al.  Relative end-effector control using Cartesian position based visual servoing , 1996, IEEE Trans. Robotics Autom..