scholarly journals Constructing a cohesive pattern for collective navigation based on a swarm of robotics

2021 ◽  
Vol 7 ◽  
pp. e626
Author(s):  
Yehia A. Soliman ◽  
Sarah N. Abdulkader ◽  
Taha M. Mohamed
Keyword(s):  
Mobile Robots ◽  
Execution Time ◽  
Swarm Robotics ◽  
Local Information ◽  
Recruitment Strategy ◽  
Central Control ◽  
Complex Tasks ◽  
Information Interaction ◽  
Collective Navigation ◽  
Swarm Size

Swarm robotics carries out complex tasks beyond the power of simple individual robots. Limited capabilities of sensing and communication by simple mobile robots have been essential inspirations for aggregation tasks. Aggregation is crucial behavior when performing complex tasks in swarm robotics systems. Many difficulties are facing the aggregation algorithm. These difficulties are as such: this algorithm has to work under the restrictions of no information about positions, no central control, and only local information interaction among robots. This paper proposed a new aggregation algorithm. This algorithm combined with the wave algorithm to achieve collective navigation and the recruitment strategy. In this work, the aggregation algorithm consists of two main phases: the searching phase, and the surrounding phase. The execution time of the proposed algorithm was analyzed. The experimental results showed that the aggregation time in the proposed algorithm was significantly reduced by 41% compared to other algorithms in the literature. Moreover, we analyzed our results using a one-way analysis of variance. Also, our results showed that the increasing swarm size significantly improved the performance of the group.

scholarly journals A Study on Various Task-Work Allocation Algorithms in Swarm Robotics

2020 ◽  
Vol 2 (2) ◽  
pp. 123-134
Author(s):  
Annamalai .L ◽  
Mohammed Siddiq. M ◽  
Ravi Shankar. S ◽  
Vigneshwar .S
Keyword(s):  
Mobile Robots ◽  
Swarm Intelligence ◽  
Task Allocation ◽  
Swarm Robotics ◽  
Entire System ◽  
Complex Tasks ◽  
Work Allocation ◽  
Allocation Algorithms

This paper discusses the various task allocation algorithms that have been researched, analyzed, and used in swarm robotics. The main reason for switching over to swarm robotics from ordinary mobile robots is because of its ability to perform complex tasks co-operatively with other bots rather than individually. Furthermore, they can be scaled to perform any kind of tasks. To carry out tasks like foraging, surveying and other such tasks that require swarm intelligence, task allocation plays an important role. It is the crux of the entire system and plays a huge role in the success of the implementation of swarm robotics. Few algorithms that address this task allocation have been briefly discussed here.

scholarly journals Holistic Connectivity Controller for Multirobot Dispersion

2013 ◽  
Vol 2013 ◽  
pp. 1-15
Author(s):  
Zhenqiang Mi ◽  
Yang Yang ◽  
Jiajia Sun
Keyword(s):  
Theoretical Analysis ◽  
Mobile Robots ◽  
Computer Simulations ◽  
Network Connectivity ◽  
Mobile Network ◽  
Local Information ◽  
Motion Controller ◽  
Multiple Agents ◽  
Entire Process ◽  
Connectivity Restoration

Dispersion of mobile robots in a certain formation is prerequisite in many applications; one of the most important issues during the entire process is to maintain the interagent connections, as well as to restore them whenever they were broken. We investigate the aforementioned problem in this work by designing a holistic connectivity controller (HCC) to regulate and restore the interagent connections during the dispersion of the mobile network. HCC consists of two core structures. Firstly, to illustrate the multirobot dispersion, we adopt the distributed link removal algorithm (DLRA), which is able to remove redundant links in the multirobot network to facilitate the dispersion and only requires local information of no more than two-hop neighbors. Secondly, the proposed approach is extended to the problem of connectivity restoration with consideration of simultaneous failure of multiple agents. A connectivity restoration strategy is proposed, and then the recoverability of network connectivity is investigated. The proposed HCC has also integrated motion controller to regulate the movement of the mobile robots, so that interrobot collisions can be effectively avoided. Theoretical analysis and computer simulations have confirmed the efficiency and scalability of the proposed schemes.

The TAM: abstracting complex tasks in swarm robotics research

2015 ◽  
Vol 9 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Arne Brutschy ◽  
Lorenzo Garattoni ◽  
Manuele Brambilla ◽  
Gianpiero Francesca ◽  
Giovanni Pini ◽  
...  
Keyword(s):  
Swarm Robotics ◽  
Complex Tasks

scholarly journals A Path-Planning Performance Comparison of RRT*-AB with MEA* in a 2-Dimensional Environment

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 945 ◽  
Author(s):  
Iram Noreen ◽  
Amna Khan ◽  
Khurshid Asghar ◽  
Zulfiqar Habib
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Execution Time ◽  
Path Length ◽  
Optimal Path ◽  
Performance Comparison ◽  
Computational Time ◽  
And Performance ◽  
Commercial Applications ◽  
Space Requirements

With the advent of mobile robots in commercial applications, the problem of path-planning has acquired significant attention from the research community. An optimal path for a mobile robot is measured by various factors such as path length, collision-free space, execution time, and the total number of turns. MEA* is an efficient variation of A* for optimal path-planning of mobile robots. RRT*-AB is a sampling-based planner with rapid convergence rate, and improved time and space requirements than other sampling-based methods such as RRT*. The purpose of this paper is the review and performance comparison of these planners based on metrics, i.e., path length, execution time, and memory requirements. All planners are tested in structured and complex unstructured environments cluttered with obstacles. Performance plots and statistical analysis have shown that MEA* requires less memory and computational time than other planners. These advantages of MEA* make it suitable for off-line applications using small robots with constrained power and memory resources. Moreover, performance plots of path length of MEA* is comparable to RRT*-AB with less execution time in the 2D environment. However, RRT*-AB will outperform MEA* in high-dimensional problems because of its inherited suitability for complex problems.

scholarly journals Collision Free Smooth Path for Mobile Robots in Cluttered Environment Using an Economical Clamped Cubic B-Spline

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1567
Author(s):  
Iram Noreen
Keyword(s):  
Mobile Robots ◽  
Execution Time ◽  
Path Length ◽  
Mobile Robotics ◽  
Optimal Path ◽  
Post Processing ◽  
B Spline ◽  
Smooth Path ◽  
Path Smoothing ◽  
Narrow Passage

Mobile robots have various applications in agriculture, autonomous cars, industrial automation, planetary exploration, security, and surveillance. The generation of the optimal smooth path is a significant aspect of mobile robotics. An optimal path for a mobile robot is measured by various factors such as path length, path smoothness, collision-free curve, execution time, and the total number of turns. However, most of the planners generate a non-smooth less optimal and linear piecewise path. Post processing smoothing is applied at the cost of increase in path length. Moreover, current research on post-processing path smoothing techniques does not address the issues of post smoothness collision and performance efficiency. This paper presents a path smoothing approach based on clamped cubic B-Spline to resolve the aforementioned issues. The proposed approach has introduced an economical point insertion scheme with automated knot vector generation while eliminating post smoothness collisions with obstacles. It generates C2 continuous path without any stitching point and passes more closely to the originally planned path. Experiments and comparison with previous approaches have shown that the proposed approach generates better results with reduced path length, and execution time. The test cases used for experiments include a simple structure environment, complex un-structured environment, an environment full of random cluttered narrow obstacles, and a case study of an indoor narrow passage.

scholarly journals Distributed Iterative Learning Formation control for Nonholonomic Multiple Wheeled Mobile Robots with Channel Noise

2021 ◽  
Vol 50 (3) ◽  
pp. 588-600
Author(s):  
Xuhui Bu ◽  
Rui Hou ◽  
Yanling Yin ◽  
Wei Yu ◽  
Jiahao Geng
Keyword(s):  
Mobile Robots ◽  
Formation Control ◽  
Tracking Error ◽  
Iterative Learning ◽  
Switching Topology ◽  
Channel Noise ◽  
Wheeled Mobile Robots ◽  
Formation Tracking ◽  
Information Interaction ◽  
The Time Domain

In this paper, we studied the robust formation control issue of multiple non-holonomic wheel mobile robots (WMRs) with nonlinear characteristics and considered the channel noise and switching communication topology, a distributed iterative learning formation control (DILFC) scheme using information interaction between robots is proposed. Firstly, the formation tracking error with consensus information is constructed, and the relationship between formation error and channel noise is obtained from the nonlinear system model of mobile robot. Next, the controller is designed based on the prediction and the current learning term between robots, and the switching topology is introduced into the formation algorithm in the form of piecewise function. The sufficient condition and norm upper bound for the formation tracking stability of the system are obtained by theoretical analysis. The results show that although the channel noise accumulates in both the time domain and iteration domain, the validity of formation tracking can be guaranteed by adjusting the sampling time of the system. To illustrate the effectiveness of the proposed scheme, numerical simulation results of a group of WMRs are presented.

scholarly journals An Introduction to Swarm Robotics

ISRN Robotics ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Iñaki Navarro ◽  
Fernando Matía
Keyword(s):  
Social Insects ◽  
Real World ◽  
Swarm Robotics ◽  
Experimental Results ◽  
Robotic Systems ◽  
Complex Tasks ◽  
Real World Applications ◽  
The Future

Swarm robotics is a field of multi-robotics in which large number of robots are coordinated in a distributed and decentralised way. It is based on the use of local rules, and simple robots compared to the complexity of the task to achieve, and inspired by social insects. Large number of simple robots can perform complex tasks in a more efficient way than a single robot, giving robustness and flexibility to the group. In this article, an overview of swarm robotics is given, describing its main properties and characteristics and comparing it to general multi-robotic systems. A review of different research works and experimental results, together with a discussion of the future swarm robotics in real world applications completes this work.

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