scholarly journals Formation and Obstacle Avoidance in the Unknown Environment of Multi-Robot System

Author(s):  
Tao Zhang ◽  
Xiaqin Li ◽  
Yi Zhu ◽  
Song Chen ◽  
Yu Cheng ◽  
...  
SIMULATION ◽  
2020 ◽  
Vol 96 (10) ◽  
pp. 807-824
Author(s):  
Jom J Kandathil ◽  
Robins Mathew ◽  
Somashekhar S Hiremath

This paper addresses the development and implementation of an obstacle avoidance strategy for a multi-robot system operating in an unknown environment. This novel strategy is based on the conventional Bug-1 obstacle avoidance algorithm, which is a non-heuristic method for obstacle avoidance in an unknown environment. In the Bug-1 algorithm, a robot circumnavigates the obstacle to find the coordinates of the point, having minimum distance to the goal. In the case of the new strategy, two robots will circumnavigate the obstacle in such a manner that it will reduce both the total travel time and the distance traveled. Information acquired by the individual robots during the circumnavigation is shared across other robots to accomplish the obstacle avoidance efficiently. A theoretical analysis is carried out to show the improvement in travel time and energy expenditure of the robots in implementing the new strategy. Different test scenarios for comparing the performance of the obstacle avoidance strategies using simulations is also identified. The simulation studies using these scenarios suggest that the new algorithm is a better algorithm with respect to multi-robot obstacle avoidance. The experimental study conducted also shows that robots using this new algorithm have a better travel time and less energy expenditure than the conventional Bug-1 algorithm.


2019 ◽  
Vol 112 ◽  
pp. 32-48 ◽  
Author(s):  
João Paulo Lima Silva de Almeida ◽  
Renan Taizo Nakashima ◽  
Flávio Neves-Jr ◽  
Lúcia Valéria Ramos de Arruda

IEEE Access ◽  
2022 ◽  
pp. 1-1
Author(s):  
Stephanie Kamarry ◽  
Raimundo Carlos S. Freire ◽  
Elyson A. N. Carvalho ◽  
Lucas Molina ◽  
Phillipe Cardoso Santos ◽  
...  

2019 ◽  
pp. 1192-1219
Author(s):  
Prithviraj Dasgupta ◽  
Taylor Whipple ◽  
Ke Cheng

This paper examines the problem of distributed coverage of an initially unknown environment using a multi-robot system. Specifically, focus is on a coverage technique for coordinating teams of multiple mobile robots that are deployed and maintained in a certain formation while covering the environment. The technique is analyzed theoretically and experimentally to verify its operation and performance within the Webots robot simulator, as well as on physical robots. Experimental results show that the described coverage technique with robot teams moving in formation can perform comparably with a technique where the robots move individually while covering the environment. The authors also quantify the effect of various parameters of the system, such as the size of the robot teams, the presence of localization, and wheel slip noise, as well as environment related features like the size of the environment and the presence of obstacles and walls on the performance of the area coverage operation.


2014 ◽  
Vol 511-512 ◽  
pp. 827-833 ◽  
Author(s):  
Martin Vondráček ◽  
Martin Dekan ◽  
František Duchoň ◽  
Stanislav Števo

The aim of this article is proposal and implementation of the multi-robot system for mapping of the unknown environment. For the localization of each robot, simple odometry was used. Navigation of the robots is based on algorithm similar to bug algorithms. Communication between robots is based on polling. The system was implemented on the platform iRobot Create. Practical experiments have proven that multi-robot system for mapping of the unknown environment is faster and more reliable than single robot system.


Robotica ◽  
2008 ◽  
Vol 26 (3) ◽  
pp. 345-356 ◽  
Author(s):  
Celso De La Cruz ◽  
Ricardo Carelli

SUMMARYThis work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.


2020 ◽  
Vol 132 ◽  
pp. 103604
Author(s):  
Ertug Olcay ◽  
Fabian Schuhmann ◽  
Boris Lohmann

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