Comparison of Heuristic Algorithms for Path Planning in 3D Printing with Multistage Experimentation System

2019 ◽  
pp. 498-510
Author(s):  
Martyna Poslednik ◽  
Iwona Pozniak-Koszalka ◽  
Leszek Koszalka ◽  
Andrzej Kasprzak
Keyword(s):  
3D Printing ◽  
Path Planning ◽  
Heuristic Algorithms

3D Printing Path Planning of Fractal Models

2018 ◽  
Vol 30 (6) ◽  
pp. 1123
Author(s):  
Xiaoya Zhai ◽  
Falai Chen
Keyword(s):  
3D Printing ◽  
Path Planning ◽  
Fractal Models

Step Ring Based 3D Path Planning via GPU Simulation for Subtractive 3D Printing

2016 ◽  
Author(s):  
Zhengkai Wu ◽  
Thomas M. Tucker ◽  
Chandra Nath ◽  
Thomas R. Kurfess ◽  
Richard W. Vuduc
Keyword(s):  
3D Printing ◽  
Path Planning ◽  
Large Scale ◽  
Cnc Machining ◽  
Scale Model ◽  
Material Surface ◽  
Processing Unit ◽  
Cad Model ◽  
Set Partition ◽  
Central Processing

In this paper, both software model visualization with path simulation and associated machining product are produced based on the step ring based 3-axis path planning to demo model-driven graphics processing unit (GPU) feature in tool path planning and 3D image model classification by GPU simulation. Subtractive 3D printing (i.e., 3D machining) is represented as integration between 3D printing modeling and CNC machining via GPU simulated software. Path planning is applied through material surface removal visualization in high resolution and 3D path simulation via ring selective path planning based on accessibility of path through pattern selection. First, the step ring selects critical features to reconstruct computer aided design (CAD) design model as STL (stereolithography) voxel, and then local optimization is attained within interested ring area for time and energy saving of GPU volume generation as compared to global all automatic path planning with longer latency. The reconstructed CAD model comes from an original sample (GATech buzz) with 2D image information. CAD model for optimization and validation is adopted to sustain manufacturing reproduction based on system simulation feedback. To avoid collision with the produced path from retraction path, we pick adaptive ring path generation and prediction in each planning iteration, which may also minimize material removal. Moreover, we did partition analysis and g-code optimization for large scale model and high density volume data. Image classification and grid analysis based on adaptive 3D tree depth are proposed for multi-level set partition of the model to define no cutting zones. After that, accessibility map is computed based on accessibility space for rotational angular space of path orientation to compare step ring based pass planning verses global all path planning. Feature analysis via central processing unit (CPU) or GPU processor for GPU map computation contributes to high performance computing and cloud computing potential through parallel computing application of subtractive 3D printing in the future.

An Intelligent 3D Printing Path Planning Algorithm 3D Printing Path Planning Algorithm

2021 ◽  
Author(s):  
Huishu Yin ◽  
Shengfa Wang ◽  
Yi Wang ◽  
Fengqi Li ◽  
Linlin Tian ◽  
...  
Keyword(s):  
3D Printing ◽  
Path Planning ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A RESEARCH ON TECHNIQUES, MODELS AND METHODS PROPOSED FOR SHIP COLLISION AVOIDANCE PATH PLANNING PROBLEM

2021 ◽  
Vol 160 (A2) ◽  
Author(s):  
R Fışkın ◽  
H Kişi ◽  
E Nasibov
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Heuristic Algorithms ◽  
Planning Problem ◽  
Related Field ◽  
Marine Industry ◽  
Soft Computing Techniques ◽  
Ship Collision ◽  
Marine Safety ◽  
Path Planning Problem

The development of soft computing techniques in recent years has encouraged researchers to study on the path planning problem in ship collision avoidance. These techniques have widely been implemented in marine industry and technology-oriented novel solutions have been introduced. Various models, methods and techniques have been proposed to solve the mentioned path planning problem with the aim of preventing reoccurrence of the problem and thus strengthening marine safety as well as providing fuel consumption efficiency. The purpose of this study is to scrutinize the models, methods and technologies proposed to settle the path planning issue in ship collision avoidance. The study also aims to provide certain bibliometric information which develops a literature map of the related field. For this purpose, a thorough literature review has been carried out. The results of the study have pointedly showed that the artificial intelligence methods, fuzzy logic and heuristic algorithms have greatly been used by the researchers who are interested in the related field.

A Research on Techniques, Models and Methods Proposed for Ship Collision Avoidance Path Planning Problem

2018 ◽  
Vol Vol 160 (A2) ◽  
Author(s):  
R Fışkın ◽  
H Kişi ◽  
E Nasibov
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Heuristic Algorithms ◽  
Planning Problem ◽  
Related Field ◽  
Marine Industry ◽  
Soft Computing Techniques ◽  
Ship Collision ◽  
Marine Safety ◽  
Path Planning Problem

The development of soft computing techniques in recent years has encouraged researchers to study on the path planning problem in ship collision avoidance. These techniques have widely been implemented in marine industry and technology-oriented novel solutions have been introduced. Various models, methods and techniques have been proposed to solve the mentioned path planning problem with the aim of preventing reoccurrence of the problem and thus strengthening marine safety as well as providing fuel consumption efficiency. The purpose of this study is to scrutinize the models, methods and technologies proposed to settle the path planning issue in ship collision avoidance. The study also aims to provide certain bibliometric information which develops a literature map of the related field. For this purpose, a thorough literature review has been carried out. The results of the study have pointedly showed that the artificial intelligence methods, fuzzy logic and heuristic algorithms have greatly been used by the researchers who are interested in the related field.

A Glowworm Swarm Optimization Algorithm for Uninhabited Combat Air Vehicle Path Planning

2015 ◽  
Vol 24 (1) ◽  
pp. 69-83 ◽  
Author(s):  
Zhonghua Tang ◽  
Yongquan Zhou
Keyword(s):  
Path Planning ◽  
Heuristic Algorithms ◽  
Optimization Methods ◽  
Pso Algorithm ◽  
Population Based ◽  
Computational Accuracy ◽  
Swarm Optimization ◽  
Glowworm Swarm Optimization ◽  
Air Vehicle ◽  
The Individual

AbstractUninhabited combat air vehicle (UCAV) path planning is a complicated, high-dimension optimization problem. To solve this problem, we present in this article an improved glowworm swarm optimization (GSO) algorithm based on the particle swarm optimization (PSO) algorithm, which we call the PGSO algorithm. In PGSO, the mechanism of a glowworm individual was modified via the individual generation mechanism of PSO. Meanwhile, to improve the presented algorithm’s convergence rate and computational accuracy, we reference the idea of parallel hybrid mutation and local search near the global optimal location. To prove the performance of the proposed algorithm, PGSO was compared with 10 other population-based optimization methods. The experiment results show that the proposed approach is more effective in UCAV path planning than most of the other meta-heuristic algorithms.

scholarly journals A Novel Method for Driving Path Planning with Spark

2021 ◽  
Author(s):  
Hao Lin
Keyword(s):  
Path Planning ◽  
Heuristic Algorithms ◽  
Parallel Design ◽  
Improve Efficiency ◽  
Novel Method ◽  
Low Efficiency

Efficient and accurate driving path planning can help drivers drive. To solve the problem of low efficiency of traditional heuristic algorithms such as PSO and GA in solving driving path planning, we introduce Excellence Coefficient into heuristic algorithms and make a parallel design based on Spark, which called EC-SPPSOGA. Excellence Coefficient can increase the probability of good edges being left, simultaneously, preserves the possibility of longer side being selected. The parallel design is based on time-consuming analysis of heuristic algorithms. We validate the performance of EC-SPPSOGA based on the data in TSPLIB. It is verified that the EC-SPPSOGA can improve efficiency of driving path planning and has good scalability.

scholarly journals Intelligent Beetle Antennae Search for UAV Sensing and Avoidance of Obstacles

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1758 ◽  
Author(s):  
Qing Wu ◽  
Xudong Shen ◽  
Yuanzhe Jin ◽  
Zeyu Chen ◽  
Shuai Li ◽  
...  
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Heuristic Algorithm ◽  
Heuristic Algorithms ◽  
Search Range ◽  
Turning Angle ◽  
Planning Algorithm ◽  
Search Speed ◽  
Path Planner ◽  
Path Planning Algorithm

Based on a bio-heuristic algorithm, this paper proposes a novel path planner called obstacle avoidance beetle antennae search (OABAS) algorithm, which is applied to the global path planning of unmanned aerial vehicles (UAVs). Compared with the previous bio-heuristic algorithms, the algorithm proposed in this paper has advantages of a wide search range and breakneck search speed, which resolves the contradictory requirements of the high computational complexity of the bio-heuristic algorithm and real-time path planning of UAVs. Besides, the constraints used by the proposed algorithm satisfy various characteristics of the path, such as shorter path length, maximum allowed turning angle, and obstacle avoidance. Ignoring the z-axis optimization by combining with the minimum threat surface (MTS), the resultant path meets the requirements of efficiency and safety. The effectiveness of the algorithm is substantiated by applying the proposed path planning algorithm on the UAVs. Moreover, comparisons with other existing algorithms further demonstrate the superiority of the proposed OABAS algorithm.

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