scholarly journals Systematic Literature Review of Swarm Robotics Strategies Applied to Target Search Problem with Environment Constraints

2021 ◽  
Vol 11 (5) ◽  
pp. 2383
Author(s):  
Zool Hilmi Ismail ◽  
Mohd Ghazali Mohd Hamami
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Swarm Robotics ◽  
Empty Space ◽  
Difficult Problem ◽  
Search Problem ◽  
Target Search ◽  
Swarm Robots ◽  
Collaboration And Communication ◽  
Target Searching

Target searching is a well-known but difficult problem in many research domains, including computational intelligence, swarm intelligence, and robotics. The main goal is to search for the targets within the specific boundary with the minimum time that is required and the obstacle avoidance that has been equipped in place. Swarm robotics (SR) is an extension of the multi-robot system that particularly discovers a concept of coordination, collaboration, and communication among a large number of robots. Because the robots are collaborating and working together, the task that is given will be completed faster compared to using a single robot. Thus, searching for single or multiple targets with swarm robots is a significant and realistic approach. Robustness, flexibility, and scalability, which are supported by distributed sensing, also make the swarm robots strategy suitable for target searching problems in real-world applications. The purpose of this article is to deliver a systematic literature review of SR strategies that are applied to target search problems, so as to show which are being explored in the fields as well as the performance of current state-of-the-art SR approaches. This review extracts data from four scientific databases and filters with two established high-indexed databases (Scopus and Web of Science). Notably, 25 selected articles fell under two main categories in environment complexity, namely empty space and cluttered. There are four strategies which have been compiled for both empty space and cluttered categories, namely, bio-inspired mechanism, behavior-based mechanism, random strategy mechanism, and hybrid mechanism.

scholarly journals Swarm Robotics Target Searching Strategy Based on Extended Bat Algorithm

2020 ◽  
Vol 2 (2) ◽  
pp. 71
Author(s):  
Nur Aisyah Syafinaz ◽  
Dwi Pebrianti ◽  
Luhur Bayuaji ◽  
Rosyati Hamid ◽  
Nurnajmin Qasrina Ann
Keyword(s):  
Swarm Robotics ◽  
Mathematical Problem ◽  
Target Position ◽  
Bat Algorithm ◽  
Communication Strategy ◽  
Searching Strategy ◽  
Swarm Robots ◽  
Target Searching ◽  
Number Of Iterations ◽  
Better Than

A swarm robotics system can consists of at least two or up to hundreds or thousands number of robots. To build a system that is able to perform target searching task, it needs a robust algoritm and communication strategy. A wrong strategy can lead to unsatisfactory performance in which the swarm robots would unable to move efficiently and arrive at the target position precisely. This work aims to develop a new method for target searching strategy for swarm robotics system by adapting Extended Bat Algorithm (EBA) to the system. EBA is the low level hybrid algorithm of Bat Algorithm (BA) and Spiral Dynamic Algoruthm (SDA), and therefore its exploration and exploitation method is better than BA and SDA. EBA had proven its ability to solve general mathematical problem, however, for swarm robotics system application, its performance and effectiveness still needs to be comprehensively investigated. The investigation result shows that EBA can prove its potentiality to develop the best target searching strategy to the swarm robotics system with 5 number of iterations within 49 seconds. This is found to be the lowest number of iterations in the shortest of time. The accuracy is 99% to arrive at the desired location. Hence, the proposed EBA method is able to perform a target searching task for swarm robotics system.

scholarly journals Toward target search approach of swarm robotics in limited communication environment based on robot chains with elimination mechanism

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142091995
Author(s):  
Yandong Luo ◽  
Jianwen Guo ◽  
Guoliang Ye ◽  
Yan Wang ◽  
Li Xie ◽  
...  
Keyword(s):  
Swarm Robotics ◽  
Search Task ◽  
Search Problem ◽  
Chain Model ◽  
Target Search ◽  
Limited Communication ◽  
Communication Environments ◽  
Search Speed ◽  
Elimination Mechanism ◽  
Search Approach

Swarm robotics refers to artificial swarm systems composed of a large number of autonomous mobile robots with relatively simple structures and functions. One of the basic problems of swarm robotics involves the target search process, which entails a cooperative search using limited perception and local interaction of robots under a self-organizing mechanism. When communication is limited, the connectivity of swarm robotics may decrease, leading to the failure of the target search task. This article describes a new target search method based on the robot chain model and the elimination mechanism. The proposed method allows the target search task to be completed efficiently and reliably while maintaining the connectivity of the robots. Experimental results show that the proposed algorithm offers better performance than conventional techniques in terms of search speed and success rate, and provides an effective method for solving the target search problem using swarm robotics in limited-communication environments.

scholarly journals A Distributed Strategy for Cooperative Autonomous Robots Using Pedestrian Behavior for Multi-Target Search in the Unknown Environment

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1606
Author(s):  
Haiyun Shi ◽  
Jie Li ◽  
Zhi Li
Keyword(s):  
Autonomous Robots ◽  
Search Problem ◽  
Collision Rate ◽  
Pedestrian Behavior ◽  
Target Search ◽  
Cooperative Strategies ◽  
Swarm Robots ◽  
Initial Location ◽  
Population Sizes ◽  
Central Coordination

Searching multiple targets with swarm robots is a realistic and significant problem. The goal is to search the targets in the minimum time while avoiding collisions with other robots. In this paper, inspired by pedestrian behavior, swarm robotic pedestrian behavior (SRPB) was proposed. It considered many realistic constraints in the multi-target search problem, including limited communication range, limited working time, unknown sources, unknown extrema, the arbitrary initial location of robots, non-oriented search, and no central coordination. The performance of different cooperative strategies was evaluated in terms of average time to find the first, the half, and the last source, the number of located sources and the collision rate. Several experiments with different target signals, fixed initial location, arbitrary initial location, different population sizes, and the different number of targets were implemented. It was demonstrated by numerous experiments that SRPB had excellent stability, quick source seeking, a high number of located sources, and a low collision rate in various search strategies.

scholarly journals A Heuristic Lowest Unknown-Degree Target Search Strategy Under Non-Structured Environment for Multi-Agent Systems

2020 ◽  
Vol 24 (7) ◽  
pp. 934-943
Author(s):  
Chunye Wang ◽  
Chen Chen ◽  
◽  
Keyword(s):  
Complex Terrain ◽  
Search Strategy ◽  
Search Problem ◽  
Multi Agent Systems ◽  
Target Search ◽  
Agent Systems ◽  
Systems Research ◽  
Structural Environment ◽  
Multi Agent ◽  
Target Searching

Multi-target searching is a hotspot and foundation topic in multi-agent systems research. However, most of the research is based on simple environment or known environment, which greatly limits the application of target search. In the non-structured environment, the searching result can be greatly affected by the complex terrain constraints and detectability of targets especially when we have no prior knowledge about the environment. In the paper, a novel search strategy combining maximum visibility and particle swarm optimization is proposed for the target search problem in a completely unknown and non-structural environment. The strategy utilizes the concept of visibility to describe how well the agent detects the map, and guides the agent to perform online path planning to complete the search task. In addition, considering the limited communication distance and communication bandwidth, the strategy introduces a cooperative mechanism for each agent to improve the search efficiency. Finally, in the experimental part, the search strategy is compared with the commonly used search strategies. Compared with the methods combining advantages, the proposed strategy can still achieve similar results, which proves the feasibility and efficiency of the strategy.

Measuring Creativity in College Students: A Systematic Literature Review (2003-2012)

2014 ◽  
Author(s):  
Heather T. Snyder ◽  
Maggie R. Boyle ◽  
Lacey Gosnell ◽  
Julia A. Hammond ◽  
Haley Huey
Keyword(s):  
College Students ◽  
Literature Review ◽  
Systematic Literature Review
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