Division of Iterative-Transportation Based on Local Observation by Multiple Mobile Robots

2012 ◽  
Vol 16 (3) ◽  
pp. 462-468
Author(s):  
Yuichi Kobayashi ◽  
◽  
Yuta Sato ◽  
Manabu Gouko ◽  
◽  
...  
Keyword(s):  
Mobile Robots ◽  
Control Law ◽  
Total Efficiency ◽  
Global Information ◽  
Centralized Control ◽  
Multiple Robots ◽  
Multiple Mobile Robots ◽  
Local Observation ◽  
Excessive Number ◽  
Explicit Communication

This paper deals with a framework of decentralized approach to division of labor by multiple mobile robots. An iterative-transportation task by multiple robots with multiple sets of starts (pick-up place of the object) and goals (put down place) is considered as the task. On each route between a start and a goal, the efficiency of transportation improves when the number of robots increases. Due to jams, however, excessive number of robots on the same route causes inefficiency. We propose a control law of each robot to choose an appropriate route so as to optimize the total efficiency of the transportation, where each robot utilizes information which can be obtained only by local observation (without any explicit communication among robots). The proposed control is based on the estimation of the number of robots on the routes in the future. In simulation, it was verified that the proposed control law realized 96% efficiency of the fully centralized control by appropriately choosing the route, compared with the case where global information can be utilized.

Division of Iterative-Transportation Based on State Estimation Using Local Observation

2012 ◽  
Vol 433-440 ◽  
pp. 5004-5011
Author(s):  
Yuta Sato ◽  
Yuichi Kobayashi ◽  
Manabu Gouko
Keyword(s):  
Mobile Robots ◽  
State Estimation ◽  
Division Of Labor ◽  
Control Law ◽  
Total Efficiency ◽  
Global Information ◽  
Multiple Robots ◽  
Local Observation ◽  
Excessive Number ◽  
Explicit Communication

This paper deals with a framework of decentralized approach to division of labor by multiple mobile robots. An iterative-transportation task by multiple robots with multiple sets of starts (pick-up place of the object) and goals (put down place) is considered as the task. On each route between a start and a goal, the efficiency of transportation improves when the number of robots increases. Due to jams, however, excessive number of robots on the same route causes inefficiency. We propose a control law of each robot to choose an appropriate route so as to optimize the total efficiency of the transportation, where each robot utilizes information which can be obtained only by local observation (without any explicit communication among robots). The proposed control is based on the estimation of the number of robots on the routes in the future by using EXPAR model. In simulation, it was verified that the proposed control law realized the similar level of the efficiency by appropriately choosing the route, compared with the case where global information can be utilized.

Cooperative Towing With Multiple Robots

2008 ◽  
Author(s):  
Jonathan Fink ◽  
Peng Cheng ◽  
Vijay Kumar
Keyword(s):  
Mobile Robots ◽  
Dry Friction ◽  
Equations Of Motion ◽  
Static Model ◽  
Multiple Robots ◽  
Coordinated Motion ◽  
Multiple Mobile Robots ◽  
Basic Concepts ◽  
Simulation Results

In this paper, we address the cooperative towing of payloads by multiple mobile robots in the plane. Robots are attached via cables to a planar object or a pallet carrying a payload. Coordinated motion by the robots allow the payload to be manipulated through a planar, warehouse-like environment. We formulate a quasi-static model for manipulation and derive equations of motion that yield the motion of the payload for a prescribed motion of the robots in the presence of dry friction and tension constraints. We present experimental and simulation results that demonstrate the basic concepts.

Environment Recognition and Path Planning by Multiple Mobile Robots

1997 ◽  
Vol 9 (5) ◽  
pp. 380-386
Author(s):  
Toshiyuki Kumaki ◽  
◽  
Masahito Nakajima ◽  
Masayoshi Kakikura ◽  
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Simulation Experiment ◽  
Distributed Coordination ◽  
Multiple Robots ◽  
Multiple Mobile Robots ◽  
Unknown Environments ◽  
Environment Recognition ◽  
Coordination Work ◽  
Observation Method

This article, concerned with a part of the research on distributed coordination work by multiple robots, discusses an algorithm for creating maps of unknown environments which are searched for and observed by multiple mobile robots, and on the results of a simulation experiment using this algorithm. This algorithm comprises a moving method, an observation method, and a task planning method which are intended to help the multiple mobile robots carry out an efficient search of unknown environments.

Flocking Task Research for Multiple Mobile Robots Based on Evolutionary Game Model

2011 ◽  
Vol 201-203 ◽  
pp. 1845-1848
Author(s):  
Ye Ye ◽  
Neng Gang Xie ◽  
Yu Wan Cen ◽  
Qing Yun Liu
Keyword(s):  
Game Theory ◽  
Mobile Robots ◽  
Evolutionary Game ◽  
Planning Problem ◽  
Game Model ◽  
Multiple Robots ◽  
Multi Objective Optimization ◽  
Multiple Mobile Robots ◽  
Coordinated Path Planning ◽  
Path Planning Problem

For flocking task of multiple mobile robots (MMR for short), the paper establishes a multi-objective optimization model and studies a solving method based on game theory. According to evolutionary game theory and taking the dynamic variability of gaming behaviors into account, it proposes a method based on evolutionary game model by using evolutionary rules “In success, commit oneself to the welfare of the society; in distress, maintain one‘s own integrity ”. Then, the paper performs researches on path coordination and obtains the optimum non-collision coordinated paths of flocking task for MMR. The simulation results show that the evolutionary game method can effectively solve coordinated path planning problem for multiple robots. By contrast with Nash equilibrium game model and coalition cooperative game model through computation results, the paper illustrates that the evolutionary game model is the best.

scholarly journals A Bio-Inspired Algorithm for Autonomous Task Coordination of Multiple Mobile Robots

Proceedings ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 1 ◽  
Author(s):  
Abhijeet Ravankar ◽  
Ankit Ravankar ◽  
Yukinori Kobayashi ◽  
Yohei Hoshino
Keyword(s):  
Mobile Robots ◽  
Service Robots ◽  
Multirobot Systems ◽  
Multiple Robots ◽  
Autonomous Exploration ◽  
Multiple Mobile Robots ◽  
Task Coordination ◽  
Task Division

Efficient task co-ordination is an important problem in multirobot systems. The explicit programming of each robot to perform specific tasks (e.g., cleaning) is too cumbersome and inefficient, as the areas to serve in a map may vary with time. Moreover, the number of available robots to serve may also vary, as some of the robots may be charging and not available. Improper task division can cause two or more robots to serve the same areas of the map, which is a waste of computation and resources. Hence, there is a need for a simpler scheme for the autonomous task co-ordination of multiple robots without the need for explicit programming. This paper presents a bioinspired algorithm that uses the attractive and repelling behavior of pheromones for autonomous task co-ordination. The proposed algorithm uses a node representation of navigational paths for autonomous exploration. This repelling mechanism also allows robots to capture areas or subareas of the map so that there is efficient task co-ordination, and robots work without interruption from other robots. We show through experiments that the proposed scheme enables multiple service robots to intelligently perform co-operative tasks without any explicit programming or commands.

Simulation Language for Multiple Mobile Robots

1997 ◽  
Vol 9 (5) ◽  
pp. 373-379
Author(s):  
Yoshinobu Adachi ◽  
◽  
Masayoshi Kakikura ◽  
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Graph Structure ◽  
Multiple Robots ◽  
Robot System ◽  
Multiple Mobile Robots ◽  
Simulation Language ◽  
Optimum Path ◽  
The Given ◽  
Planning Problems

The purpose of this paper is to propose a design concept for a simulation language to be used in path planning in a multiple mobile robots system. The paper also includes some examples of programming of path planning for multiple mobile robots. In some path planning problems with mobile robots, graph theory can be a powerful tool. In our system, the environment information of the robots is represented in a graph structure. By handling this graph with a programming language, path planning tasks can be executed in a systematic way. Each task of the multiple mobile robots can be described using a Petrinet expression, and several features of the given robot system, for example, the optimum path problem, the deadlock problem of multiple robots, etc., can be deduced using the network model.

Cooperative Towing With Multiple Robots

2008 ◽  
Vol 1 (1) ◽  
Author(s):  
Peng Cheng ◽  
Jonathan Fink ◽  
Vijay Kumar ◽  
Jong-Shi Pang
Keyword(s):  
Mobile Robots ◽  
Dry Friction ◽  
Equations Of Motion ◽  
Experimental Results ◽  
Multiple Robots ◽  
Multiple Mobile Robots ◽  
Basic Concepts

In this paper, we address the cooperative towing of payloads by multiple mobile robots that move in the plane. Robots are attached via cables to an object or a pallet carrying a payload, and they coordinate their motion to manipulate the payload through a planar warehouselike environment. We formulate a quasistatic model for manipulation and derive equations of motion that yield the motion of the payload for a prescribed motion of the robots in the presence of dry friction and tension constraints. We present the experimental results that demonstrate the basic concepts.

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