Automated Planning for Robotic Multi-Resolution Additive Manufacturing

Author(s):  
Prahar Bhatt ◽  
Ashish Kulkarni ◽  
Rishi K. Malhan ◽  
Brual Shah ◽  
Yeo Jung Yoon ◽  
...  

Abstract Conventional material extrusion additive manufacturing (AM) processes require the user to make a trade-off between surface quality and build time of the part. The use of a large bead filament deposition can speed up the build process; however, it leads to surfaces with high roughness due to the stair-stepping effect. The surface quality can be improved by using a small bead filament deposition, which in turn increases the build time of the part. We present a new approach incorporating hybrid multi-resolution layers in material extrusion additive manufacturing to provide excellent surface quality without increasing the build time. Our slicing algorithm generates planar layers with large filament to fill the interior regions in less time. The generated exterior layers are conformal and use small filament to reduce the stair-stepping effect and improve surface quality. We also present a path planning algorithm to build parts with a single manipulator using a multi-nozzle extrusion tool. The path planning algorithm generates a smooth material deposition path by avoiding collision between the tool and the already built layers. It reduces the collision checks and performs collision detection in a computationally efficient manner. We build five parts to validate our approach and illustrate the benefits of multi-resolution AM.

2021 ◽  
Vol 11 (13) ◽  
pp. 5759
Author(s):  
Markus Schmitz ◽  
Jan Wiartalla ◽  
Markus Gelfgren ◽  
Samuel Mann ◽  
Burkhard Corves ◽  
...  

Previous algorithms for slicing, path planning or trajectory planning of additive manufacturing cannot be used consistently for multidirectional additive manufacturing with pure object manipulation in wire-arc additive manufacturing. This work presents a novel path planning approach that directly takes robot kinematics into account and thus ensures the reachability of all critical path poses. In an additional step, the planned path segments are smoothed so that joint velocity limits are respected. It is shown that the implemented path planner generates executable robot paths and at the same time maintains the process quality (in this case, sufficient coverage of the slice area). While the introduced method enables the generation of reachable printing paths, the smoothing algorithm allows for the execution of the path with respect to the robot’s velocity limits and at the same time improves the slice coverage. Future experiments will show the realization of the real robot setup presented.


2020 ◽  
Vol 83 (1) ◽  
pp. 133-143
Author(s):  
Sanjoy Kumar Debnath ◽  
Rosli Omar ◽  
Nor Badariyah Abdul Latip ◽  
Susama Bagchi ◽  
Elia Nadira Sabudin ◽  
...  

This paper analyses an experimental path planning performance between the Iterative Equilateral Space Oriented Visibility Graph (IESOVG) and conventional Visibility Graph (VG) algorithms in terms of computation time and path length for an autonomous vehicle. IESOVG is a path planning algorithm that was proposed to overcome the limitations of VG which is slow in obstacle-rich environment. The performance assessment was done in several identical scenarios through simulation. The results showed that the proposed IESOVG algorithm was much faster in comparison to VG. In terms of path length, IESOVG was found to have almost similar performance with VG.  It was also found that IESOVG was complete as it could find a collision-free path in all scenarios.


2015 ◽  
Vol 65 (6) ◽  
pp. 483 ◽  
Author(s):  
Daniel-Ioan Curiac ◽  
Constantin Volosencu

During their task accomplishment, autonomous unmanned aerial vehicles are facing more and more threats coming from both ground and air. In such adversarial environments, with no a priori information about the threats, a flying robot in charge with surveilling a specified 3D sector must perform its tasks by evolving on misleading and unpredictable trajectories to cope with enemy entities. In our view, the chaotic dynamics can be the cornerstone in designing unpredictable paths for such missions, even though this solution was not exploited until now by researchers in the 3D context. This paper addresses the flight path-planning issue for surveilling a given volume in adversarial conditions by proposing a proficient approach that uses the chaotic behaviour exhibited by the 3D Arnold’s cat map. By knowing the exact location of the volume under surveillance before take-off, the flying robot will generate the successive chaotic waypoints only with onboard resources, in an efficient manner. The method is validated by simulation in a realistic scenario using a detailed Simulink model for the X-4 Flyer quadcopter.


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