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Swarm Robotics
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Swarm Robotics

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (31 August 2018) | Viewed by 71357

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Dr. Giandomenico Spezzano

E-Mail Website
Guest Editor
National Research Council of Italy (CNR), Institute for High Performance Computing and Networking (ICAR), Via Pietro Bucci, 8-9C, 87036 Rende, CS, Italy
Interests: Internet of Things; learning (artificial intelligence); energy management systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Swarm robotics is a new approach to coordinate the behaviors of large numbers of relatively simple robots in a decentralized manner. It is based on the use of local rules and robots that are simple in comparison to the complexity of the task to achieve, and is inspired by social insects. Large numbers of simple robots can perform complex tasks in a more efficient way than a single robot, giving robustness and flexibility to the group. Robotic systems built on swarm intelligence show high efficiency, parallelism, scalability and robustness.

The area of swarm robotics will also benefit from the Internet of Things (IoT). Swarm robots will be able to communicate with each other and other objects around them through the cloud. The computational power will be supplied in the cloud and many of the robotic sensors required will be available from objects around them.

The potential applications of swarm robotics include tasks that demand miniaturization, like distributed sensing tasks in micro machinery or the human body. On the other hand, swarm robotics may be suited to the tasks that demand cheap designs, such as mining or agricultural foraging. Swarm robotics can be also involved in tasks that require large space and time costs and are dangerous to human beings or the robots themselves, such as post-disaster relief, target searching, or military applications.

In this Special Issue we want to address recent advances in the following topics:

  • Challenges and problems in swarm robotics

  • Advances in swarm robotics

  • Cooperative control

  • Modeling and simulation

  • Swarm intelligence

  • Design of emergence

  • Swarms of drones

  • Biomimetics and bio-inspired robotics

  • Multi-agent systems

  • Decentralized control and distributed systems

  • Modeling methods for swarm robotics

  • Self-organization and self-assembly

  • Collective movement and task allocation

  • Control algorithm for drone swarms

  • Collective transport of objects

  • Collective mapping

  • Swarm robotics and behavior models

  • Local  sensing and communications

  • Safety analysis of swarm robotics

  • Develop methodologies and practises

  • Swarm of medical nanorobots for fight cancer

  • Robot algorithms development (software)

  • Cooperative Robotics in IoT Ecosystems

  • The Internet of Robotic Things

Submissions are invited for both original research and review articles. Additionally, invited papers based on excellent contributions to recent conferences in this field will be included in this Special Issue. It is hoped that this collection of high-quality works in swarm robotics will serve as an inspiration for future research in this field.

Dr. Giandomenico Spezzano
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Swarms of drones

  • Artificial intelligence

  • Machine learning

  • Cooperative control

  • Bio-inspired algorithms

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Published Papers (16 papers)

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Editorial

Jump to: Research

3 pages, 146 KiB  
Editorial
Editorial: Special Issue “Swarm Robotics”
by Giandomenico Spezzano
Appl. Sci. 2019, 9(7), 1474; https://doi.org/10.3390/app9071474 - 9 Apr 2019
Cited by 7 | Viewed by 2717
Abstract
Swarm robotics is the study of how to coordinate large groups of relatively simple robots through the use of local rules so that a desired collective behavior emerges from their interaction [...] Full article
(This article belongs to the Special Issue Swarm Robotics)

Research

Jump to: Editorial

17 pages, 7023 KiB  
Article
V-Shaped Formation Control for Robotic Swarms Constrained by Field of View
by Jian Yang, Xin Wang and Peter Bauer
Appl. Sci. 2018, 8(11), 2120; https://doi.org/10.3390/app8112120 - 1 Nov 2018
Cited by 30 | Viewed by 3889
Abstract
By forming a specific formation during motion, the robotic swarm is a good candidate for unknown region exploration applications. The members of this kind of system are generally low complexity, which limits the communication and perception capacities of the agents. How to merge [...] Read more.
By forming a specific formation during motion, the robotic swarm is a good candidate for unknown region exploration applications. The members of this kind of system are generally low complexity, which limits the communication and perception capacities of the agents. How to merge to the desired formation under those constraints is essential for performing relevant tasks. In this paper, a limited visual field constrained formation control strategy inspired by flying geese coordinated motion is introduced. Usually, they flock together in a V-shape formations, which is a well-studied phenomenon in biology and bionics. This paper illustrates the proposed methods by taking the research results from the above subjects and mapping them from the swarm engineering point of view. The formation control is achieved by applying a behavior-based formation forming method with the finite state machine while considering anti-collision and obstacle avoidance. Furthermore, a cascade leader–follower structure is adopted to achieve the large-scale formations. The simulation results from several scenarios indicate the presented method is robust with high scalability and flexibility. Full article
(This article belongs to the Special Issue Swarm Robotics)
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17 pages, 4618 KiB  
Article
Decentralization of Virtual Linkage in Formation Control of Multi-Agents via Consensus Strategies
by Yi Liu, Junyao Gao, Xuanyang Shi and Chunyu Jiang
Appl. Sci. 2018, 8(11), 2020; https://doi.org/10.3390/app8112020 - 23 Oct 2018
Cited by 14 | Viewed by 3036
Abstract
Featured Application: This paper addresses the formation control of a team of agents based on the decentralized control and the recently introduced reconfigurable virtual linkage approach. Following a decentralized control architecture, a decentralized virtual linkage approach is introduced. As compared to the original [...] Read more.
Featured Application: This paper addresses the formation control of a team of agents based on the decentralized control and the recently introduced reconfigurable virtual linkage approach. Following a decentralized control architecture, a decentralized virtual linkage approach is introduced. As compared to the original virtual linkage approach, the proposed approach uses decentralized architecture rather than hierarchical architecture, which does not require role assignments in each virtual link. In addition, each agent can completely decide its movement with only exchanging states with part of the team members, which makes this approach more suitable for situations when a large number of agents and/or limited communication are involved. Furthermore, the reconfiguration ability is enhanced in this approach by introducing the scale factor of each virtual link. Finally, the effectiveness of the proposed method is demonstrated through simulation results. Full article
(This article belongs to the Special Issue Swarm Robotics)
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20 pages, 7249 KiB  
Article
SambotII: A New Self-Assembly Modular Robot Platform Based on Sambot
by Wenshuai Tan, Hongxing Wei and Bo Yang
Appl. Sci. 2018, 8(10), 1719; https://doi.org/10.3390/app8101719 - 21 Sep 2018
Cited by 9 | Viewed by 3972
Abstract
A new self-assembly modular robot (SMR) SambotII is developed based on SambotI, which is a previously-built hybird type SMR that is capable of autonomous movement and self-assembly. As is known, SambotI only has limited abilities of environmental perception and target recognition, because its [...] Read more.
A new self-assembly modular robot (SMR) SambotII is developed based on SambotI, which is a previously-built hybird type SMR that is capable of autonomous movement and self-assembly. As is known, SambotI only has limited abilities of environmental perception and target recognition, because its STM-32 processor cannot handle heavy work, like image processing and path planning. To improve the computing ability, an x86 dual-core CPU is applied and a hierarchical software architecture with five layers is designed. In addition, to enhance its perception abilities, a laser-camera unit and a LED-camera unit are employed to obtain the distance and angle information, respectively, and the color-changeable LED lights are used to identify different passive docking surfaces during the docking process. Finally, the performances of SambotII are verified by docking experiments. Full article
(This article belongs to the Special Issue Swarm Robotics)
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17 pages, 861 KiB  
Article
Event-Driven Sensor Deployment in an Underwater Environment Using a Distributed Hybrid Fish Swarm Optimization Algorithm
by Hui Wang, Youming Li, Tingcheng Chang, Shengming Chang and Yexian Fan
Appl. Sci. 2018, 8(9), 1638; https://doi.org/10.3390/app8091638 - 13 Sep 2018
Cited by 16 | Viewed by 3335
Abstract
In open and complex underwater environments, targets to be monitored are highly dynamic and exhibit great uncertainty. To optimize monitoring target coverage, the development of a method for adjusting sensor positions based on environments and targets is of crucial importance. In this paper, [...] Read more.
In open and complex underwater environments, targets to be monitored are highly dynamic and exhibit great uncertainty. To optimize monitoring target coverage, the development of a method for adjusting sensor positions based on environments and targets is of crucial importance. In this paper, we propose a distributed hybrid fish swarm optimization algorithm (DHFSOA) based on the influence of water flow and the operation of an artificial fish swarm system to improve the coverage efficacy of the event set and to avoid blind movements of sensor nodes. First, by simulating the behavior of foraging fish, sensor nodes autonomously tend to cover events, with congestion control being used to match node distribution density to event distribution density. Second, the construction of an information pool is used to achieve information-sharing between nodes within the network connection range, to increase the nodes’ field of vision, and to enhance their global search abilities. Finally, we conduct extensive simulation experiments to evaluate network performance in different deployment environments. The results show that the proposed DHFSOA performs well in terms of coverage efficacy, energy efficiency, and convergence rate of the event set. Full article
(This article belongs to the Special Issue Swarm Robotics)
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12 pages, 631 KiB  
Article
Real-Time Swarm Search Method for Real-World Quadcopter Drones
by Ki-Baek Lee, Young-Joo Kim and Young-Dae Hong
Appl. Sci. 2018, 8(7), 1169; https://doi.org/10.3390/app8071169 - 18 Jul 2018
Cited by 18 | Viewed by 5592
Abstract
This paper proposes a novel search method for a swarm of quadcopter drones. In the proposed method, inspired by the phenomena of swarms in nature, drones effectively look for the search target by investigating the evidence from the surroundings and communicating with each [...] Read more.
This paper proposes a novel search method for a swarm of quadcopter drones. In the proposed method, inspired by the phenomena of swarms in nature, drones effectively look for the search target by investigating the evidence from the surroundings and communicating with each other. The position update mechanism is implemented using the particle swarm optimization algorithm as the swarm intelligence (a well-known swarm-based optimization algorithm), as well as a dynamic model for the drones to take the real-world environment into account. In addition, the mechanism is processed in real-time along with the movements of the drones. The effectiveness of the proposed method was verified through repeated test simulations, including a benchmark function optimization and air pollutant search problems. The results show that the proposed method is highly practical, accurate, and robust. Full article
(This article belongs to the Special Issue Swarm Robotics)
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25 pages, 9931 KiB  
Article
Reconfigurable Formation Control of Multi-Agents Using Virtual Linkage Approach
by Yi Liu, Junyao Gao, Cunqiu Liu, Fangzhou Zhao and Jingchao Zhao
Appl. Sci. 2018, 8(7), 1109; https://doi.org/10.3390/app8071109 - 9 Jul 2018
Cited by 14 | Viewed by 3745
Abstract
Formation control is an important problem in cooperative robotics due to its broad applications. To address this problem, the concept of a virtual linkage is introduced. Using this idea, a group of robots is designed and controlled to behave as particles embedded in [...] Read more.
Formation control is an important problem in cooperative robotics due to its broad applications. To address this problem, the concept of a virtual linkage is introduced. Using this idea, a group of robots is designed and controlled to behave as particles embedded in a mechanical linkage instead of as a single rigid body as with the virtual structure approach. As compared to the virtual structure approach, the method proposed here can reconfigure the group of robots into different formation patterns by coordinating the joint angles in the corresponding mechanical linkage. Meanwhile, there is no need to transmit all the robots’ state information to a single location and implement all of the computation on it, due to virtual linkage’s hierarchical architecture. Finally, the effectiveness of the proposed method is demonstrated using two simulations with nine robots: moving around a circle in line formation, and moving through a gallery with varying formation patterns. Full article
(This article belongs to the Special Issue Swarm Robotics)
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16 pages, 3375 KiB  
Article
Leader–Follower Formation Maneuvers for Multi-Robot Systems via Derivative and Integral Terminal Sliding Mode
by Dianwei Qian and Yafei Xi
Appl. Sci. 2018, 8(7), 1045; https://doi.org/10.3390/app8071045 - 27 Jun 2018
Cited by 20 | Viewed by 5107
Abstract
This paper investigates the formation problem of multiple robots based on the leader–follower mechanism. At first, the dynamics of such a leader–follower framework are modeled. The input–output equations are depicted by calculating the relative degree of a leader–follower formation system. Furthermore, the derivative [...] Read more.
This paper investigates the formation problem of multiple robots based on the leader–follower mechanism. At first, the dynamics of such a leader–follower framework are modeled. The input–output equations are depicted by calculating the relative degree of a leader–follower formation system. Furthermore, the derivative and integral terminal sliding mode controller is designed based on the relative degree. Since the formation system suffers from uncertainties, the nonlinear disturbance observer is adopted to deal with the uncertainties. The stability of the closed-loop control system is proven in the sense of Lyapunov. Finally, some numerical simulations are displayed to verify the feasibility and effectiveness by the designed controller and observer. Full article
(This article belongs to the Special Issue Swarm Robotics)
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Graphical abstract

17 pages, 6090 KiB  
Article
Optimal Configuration and Path Planning for UAV Swarms Using a Novel Localization Approach
by Weijia Wang, Peng Bai, Hao Li and Xiaolong Liang
Appl. Sci. 2018, 8(6), 1001; https://doi.org/10.3390/app8061001 - 19 Jun 2018
Cited by 14 | Viewed by 4815
Abstract
In localization estimation systems, it is well known that the sensor-emitter geometry can seriously impact the accuracy of the location estimate. In this paper, time-difference-of-arrival (TDOA) localization is applied to locate the emitter using unmanned aerial vehicle (UAV) swarms equipped with TDOA-based sensors. [...] Read more.
In localization estimation systems, it is well known that the sensor-emitter geometry can seriously impact the accuracy of the location estimate. In this paper, time-difference-of-arrival (TDOA) localization is applied to locate the emitter using unmanned aerial vehicle (UAV) swarms equipped with TDOA-based sensors. Different from existing studies where the variance of measurement noises is assumed to be independent and changeless, we consider a more realistic model where the variance is sensor-emitter distance-dependent. First, the measurements model and variance model based on signal-to-noise ratio (SNR) are considered. Then the Cramer–Rao low bound (CRLB) is calculated and the optimal configuration is analyzed via the distance rule and angle rule. The sensor management problem of optimizing UAVs trajectories is studied by generating a sequence of waypoints based on CRLB. Simulation results show that path optimization enhances the localization accuracy and stability. Full article
(This article belongs to the Special Issue Swarm Robotics)
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23 pages, 1619 KiB  
Article
Signal Source Localization of Multiple Robots Using an Event-Triggered Communication Scheme
by Ligang Pan, Qiang Lu, Ke Yin and Botao Zhang
Appl. Sci. 2018, 8(6), 977; https://doi.org/10.3390/app8060977 - 14 Jun 2018
Cited by 15 | Viewed by 3538
Abstract
This paper deals with the problem of signal source localization using a group of autonomous robots by designing and analyzing a decision-control approach with an event-triggered communication scheme. The proposed decision-control approach includes two levels: a decision level and a control level. In [...] Read more.
This paper deals with the problem of signal source localization using a group of autonomous robots by designing and analyzing a decision-control approach with an event-triggered communication scheme. The proposed decision-control approach includes two levels: a decision level and a control level. In the decision level, a particle filter is used to estimate the possible positions of the signal source. The estimated position of the signal source gradually approaches the real position of signal source with the movement of robots. In the control level, a consensus controller is proposed to control multiple robots to seek a signal source based on the estimated signal source position. At the same time, an event-triggered communication scheme is designed such that the burden of communication can be lightened. Finally, simulation and experimental results show the effectiveness of the proposed decision-control approach with the event-triggered communication scheme for the problem of signal source localization. Full article
(This article belongs to the Special Issue Swarm Robotics)
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12 pages, 3533 KiB  
Article
Multi-AUV Cooperative Target Hunting Based on Improved Potential Field in a Surface-Water Environment
by Hengqing Ge, Guibin Chen and Guang Xu
Appl. Sci. 2018, 8(6), 973; https://doi.org/10.3390/app8060973 - 14 Jun 2018
Cited by 34 | Viewed by 4110
Abstract
In this paper, target hunting aims to detect target and surround the detected target in a surface-water using Multiple Autonomous Underwater Vehicles (multi-AUV) in a given area. The main challenge in multi-AUV target hunting is the design of AUV’s motion path and coordination [...] Read more.
In this paper, target hunting aims to detect target and surround the detected target in a surface-water using Multiple Autonomous Underwater Vehicles (multi-AUV) in a given area. The main challenge in multi-AUV target hunting is the design of AUV’s motion path and coordination mechanism. To conduct the cooperative target hunting by multi-AUV in a surface-water environment, an integrated algorithm based on improved potential field (IPF) is proposed. First, a potential field function is established according to the information of the surface-water environment. Then, the dispersion degree, the homodromous degree, and district-difference degree are introduced to increase the cooperation of the multi-AUV system. Finally, the target hunting is solved by embedding the three kinds of degree into the potential field function. The simulation results show that the proposed approach is applicable and feasible for multi-AUV cooperative target hunting. Full article
(This article belongs to the Special Issue Swarm Robotics)
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31 pages, 25646 KiB  
Article
Exploration of Swarm Dynamics Emerging from Asymmetry
by Naoki Nishikawa, Reiji Suzuki and Takaya Arita
Appl. Sci. 2018, 8(5), 729; https://doi.org/10.3390/app8050729 - 5 May 2018
Cited by 5 | Viewed by 4728
Abstract
A swarm might exhibit interesting motions or structures when it includes different types of agents. On a swarm model named Swarm Chemistry, some interesting patterns can appear if the parameters are well-tuned. However, there is a hurdle for us to get capable of [...] Read more.
A swarm might exhibit interesting motions or structures when it includes different types of agents. On a swarm model named Swarm Chemistry, some interesting patterns can appear if the parameters are well-tuned. However, there is a hurdle for us to get capable of tuning the parameters by automatic searching methods like a genetic algorithm, particularly because defining interestingness itself is a challenging issue. This paper aims to investigate how interesting patterns can be detected, comparing seven measures from an aspect of system asymmetries. Based on numerical experiments, the effects of changing kinetic parameters are discussed, finding that: (1) segregating patterns, which are frequently observed but uninteresting, tend to appear when the perception range is small and normal (ideal) speed is large or when cohesive force is weak and separating force is strong; (2) asymmetry of information transfer represented by topological connectivity is an effective way to characterize the interestingness; (3) pulsation-like patterns can be captured well by using time-derivative of state variables like network-degrees; (4) it helps capture a gradual structural deformation when fitness function adopts the mean over min-max differences of state variables. The findings will help the efficient search of already-discovered or undiscovered interesting swarm dynamics. Full article
(This article belongs to the Special Issue Swarm Robotics)
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31 pages, 1000 KiB  
Article
Comparison of Heuristic Algorithms in Discrete Search and Surveillance Tasks Using Aerial Swarms
by Pablo Garcia-Aunon and Antonio Barrientos Cruz
Appl. Sci. 2018, 8(5), 711; https://doi.org/10.3390/app8050711 - 3 May 2018
Cited by 15 | Viewed by 4234
Abstract
The search of a given area is one of the most studied tasks in swarm robotics. Different heuristic methods have been studied in the past taking into account the peculiarities of these systems (number of robots, limited communications and sensing and computational capacities). [...] Read more.
The search of a given area is one of the most studied tasks in swarm robotics. Different heuristic methods have been studied in the past taking into account the peculiarities of these systems (number of robots, limited communications and sensing and computational capacities). In this work, we introduce a behavioral network made up of different well-known behaviors that act together to achieve a good performance, while adapting to different scenarios. The algorithm is compared with six strategies based on movement patterns in terms of three performance models. For the comparison, four scenario types are considered: plain, with obstacles, with the target location probability distribution and a combination of obstacles and the target location probability distribution. For each scenario type, different variations are considered, such as the number of agents and area size. Results show that although simplistic solutions may be convenient for the simplest scenario type, for the more complex ones, the proposed algorithm achieves better results. Full article
(This article belongs to the Special Issue Swarm Robotics)
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22 pages, 6976 KiB  
Article
Artificial Flora (AF) Optimization Algorithm
by Long Cheng, Xue-han Wu and Yan Wang
Appl. Sci. 2018, 8(3), 329; https://doi.org/10.3390/app8030329 - 26 Feb 2018
Cited by 93 | Viewed by 7734
Abstract
Inspired by the process of migration and reproduction of flora, this paper proposes a novel artificial flora (AF) algorithm. This algorithm can be used to solve some complex, non-linear, discrete optimization problems. Although a plant cannot move, it can spread seeds within a [...] Read more.
Inspired by the process of migration and reproduction of flora, this paper proposes a novel artificial flora (AF) algorithm. This algorithm can be used to solve some complex, non-linear, discrete optimization problems. Although a plant cannot move, it can spread seeds within a certain range to let offspring to find the most suitable environment. The stochastic process is easy to copy, and the spreading space is vast; therefore, it is suitable for applying in intelligent optimization algorithm. First, the algorithm randomly generates the original plant, including its position and the propagation distance. Then, the position and the propagation distance of the original plant as parameters are substituted in the propagation function to generate offspring plants. Finally, the optimal offspring is selected as a new original plant through the selection function. The previous original plant becomes the former plant. The iteration continues until we find out optimal solution. In this paper, six classical evaluation functions are used as the benchmark functions. The simulation results show that proposed algorithm has high accuracy and stability compared with the classical particle swarm optimization and artificial bee colony algorithm. Full article
(This article belongs to the Special Issue Swarm Robotics)
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25 pages, 445 KiB  
Article
Parallel Technique for the Metaheuristic Algorithms Using Devoted Local Search and Manipulating the Solutions Space
by Dawid Połap, Karolina Kęsik, Marcin Woźniak and Robertas Damaševičius
Appl. Sci. 2018, 8(2), 293; https://doi.org/10.3390/app8020293 - 16 Feb 2018
Cited by 29 | Viewed by 4319
Abstract
The increasing exploration of alternative methods for solving optimization problems causes that parallelization and modification of the existing algorithms are necessary. Obtaining the right solution using the meta-heuristic algorithm may require long operating time or a large number of iterations or individuals in [...] Read more.
The increasing exploration of alternative methods for solving optimization problems causes that parallelization and modification of the existing algorithms are necessary. Obtaining the right solution using the meta-heuristic algorithm may require long operating time or a large number of iterations or individuals in a population. The higher the number, the longer the operation time. In order to minimize not only the time, but also the value of the parameters we suggest three proposition to increase the efficiency of classical methods. The first one is to use the method of searching through the neighborhood in order to minimize the solution space exploration. Moreover, task distribution between threads and CPU cores can affect the speed of the algorithm and therefore make it work more efficiently. The second proposition involves manipulating the solutions space to minimize the number of calculations. In addition, the third proposition is the combination of the previous two. All propositions has been described, tested and analyzed due to the use of various test functions. Experimental research results show that the proposed methodology for parallelization and manipulation of solution space is efficient (increasing the accuracy of solutions and reducing performance time) and it is possible to apply it also to other optimization methods. Full article
(This article belongs to the Special Issue Swarm Robotics)
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2116 KiB  
Article
3D Model Identification Using Weighted Implicit Shape Representation and Panoramic View
by Xun Jin and Jongweon Kim
Appl. Sci. 2017, 7(8), 764; https://doi.org/10.3390/app7080764 - 27 Jul 2017
Cited by 5 | Viewed by 4449
Abstract
In this paper, we propose a 3 dimensional (3D) model identification method based on weighted implicit shape representation (WISR) and panoramic view. The WISR is used for 3D shape normalization. The 3D shape normalization method normalizes a 3D model by scaling, translation, and [...] Read more.
In this paper, we propose a 3 dimensional (3D) model identification method based on weighted implicit shape representation (WISR) and panoramic view. The WISR is used for 3D shape normalization. The 3D shape normalization method normalizes a 3D model by scaling, translation, and rotation with respect to the scale factor, center, and principal axes. The major advantage of the WISR is reduction of the influences caused by shape deformation and partial removal. The well-known scale-invariant feature transform descriptors are extracted from the panoramic view of the 3D model for feature matching. The panoramic view is a range image obtained by projecting a 3D model to the surface of a cylinder which is parallel to a principal axis determined by the 3D shape normalization. Because of using only one range image, the proposed method can provide small size of features and fast matching speed. The precision of the identification is 92% with 1200 models that consist of 24 deformed versions of 50 classes. The average feature size and matching time are 4.1 KB and 1.9 s. Full article
(This article belongs to the Special Issue Swarm Robotics)
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