scholarly journals TWO-LAYERS WORKSPACE: A NEW APPROACH TO COOPERATIVE OBJECT TRANSPORTATION WITH OBSTACLE AVOIDANCE FOR MULTI-ROBOT SYSTEM

IEEE Access ◽  
2022 ◽  
pp. 1-1
Author(s):  
Stephanie Kamarry ◽  
Raimundo Carlos S. Freire ◽  
Elyson A. N. Carvalho ◽  
Lucas Molina ◽  
Phillipe Cardoso Santos ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Robot System ◽  
New Approach ◽  
Object Transportation ◽  
Multi Robot

Dynamic model based formation control and obstacle avoidance of multi-robot systems

Robotica ◽  
2008 ◽  
Vol 26 (3) ◽  
pp. 345-356 ◽  
Author(s):  
Celso De La Cruz ◽  
Ricardo Carelli
Keyword(s):  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Formation Control ◽  
Inverse Dynamics ◽  
Single Equation ◽  
Model Parameters ◽  
Robot System ◽  
System A ◽  
Robot Systems ◽  
Multi Robot

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.

Multi-Robot Cooperative Transportation of Objects Using Modified Q-Learning

2010 ◽  
Author(s):  
Pallege Gamini Dilupa Siriwardana ◽  
Clarence de Silva
Keyword(s):  
Autonomous Robots ◽  
Dynamic Environment ◽  
Learning Approach ◽  
Robot System ◽  
Q Learning ◽  
Time Performance ◽  
Object Pose Estimation ◽  
Object Transportation ◽  
Blob Tracking ◽  
Multi Robot

In cooperative multi-robot object transportation, several autonomous robots navigate cooperatively in either a static or a dynamic environment to transport an object to a goal location and orientation. The environment may consist of both fixed and removable obstacles and it will be subject to uncertainty and unforeseen changes within the environment. More than one robot may be required for handling heavy and large objects. This paper presents a modified Q-learning approach for object transportation utilizing cooperative and autonomous multiple mobile robots. A modified version of Q-learning is presented, which employs for effective robot coordination. A solution to the action selection conflicts of the robots is presented, which helps to improve the real time performance and robustness of the system. As required in the task, the paper presents an algorithm for object pose estimation, by utilizing the laser range finder and color blob tracking. The developed techniques are implemented in a multi-robot system in laboratory. Experimental results are presented to demonstrate the effectiveness of the developed multi-robot system and its underlying methodologies.

scholarly journals Modified bug-1 algorithm based strategy for obstacle avoidance in multi robot system

2018 ◽  
Vol 144 ◽  
pp. 01012 ◽  
Author(s):  
Jom J. Kandathil ◽  
Robins Mathew ◽  
Somashekhar S. Hiremath
Keyword(s):  
Obstacle Avoidance ◽  
Target Location ◽  
Search Algorithm ◽  
Global Knowledge ◽  
Robot System ◽  
Practical Applications ◽  
Global Goal ◽  
Starting Location ◽  
Start Location ◽  
Multi Robot

One of the primary ability of an intelligent mobile robot system is obstacle avoidance. BUG algorithms are classic examples of the algorithms used for achieving obstacle avoidance. Unlike many other planning algorithms based on global knowledge, BUG algorithms assume only local knowledge of the environment and a global goal. Among the variations of the BUG algorithms that prevail, BUG-0, BUG-1 and BUG-2 are the more prominent versions. The exhaustive search algorithm present in BUG-1 makes it more reliable and safer for practical applications. Overall, this provides a more predictable and dependable performance. Hence, the essential focus in this paper is on implementing the BUG-1 algorithm across a group of robots to move them from a start location to a target location. The results are compared with the results from BUG-1 algorithm implemented on a single robot. The strategy developed in this work reduces the time involved in moving the robots from starting location to the target location. Further, the paper shows that the total distance covered by each robot in a multi robot-system is always lesser than or equal to that travelled by a single robot executing the same problem.

Object Transportation Using a Cooperative Mobile Multi-Robot System

2016 ◽  
Vol 14 (3) ◽  
pp. 1184-1191 ◽  
Author(s):  
A.G. Barrientos ◽  
J.L. Lopez ◽  
E.S. Espinoza ◽  
J. Hoyo ◽  
G. Valencia
Keyword(s):  
Robot System ◽  
Object Transportation ◽  
Multi Robot

Development and analysis of a novel obstacle avoidance strategy for a multi-robot system inspired by the Bug-1 algorithm

SIMULATION ◽  
2020 ◽  
Vol 96 (10) ◽  
pp. 807-824
Author(s):  
Jom J Kandathil ◽  
Robins Mathew ◽  
Somashekhar S Hiremath
Keyword(s):  
Energy Expenditure ◽  
Travel Time ◽  
Obstacle Avoidance ◽  
Heuristic Method ◽  
Robot System ◽  
Unknown Environment ◽  
New Strategy ◽  
Total Travel Time ◽  
Avoidance Strategy ◽  
Multi Robot

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.

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