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.

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.

Collision-free trajectory control for multiple robots based on neural optimization network

Robotica ◽  
1990 ◽  
Vol 8 (3) ◽  
pp. 185-194 ◽  
Author(s):  
Jihong Lee ◽  
Zeungnam Bien
Keyword(s):  
Differential Equation ◽  
Mobile Robots ◽  
Neural Circuit ◽  
Heuristic Method ◽  
Trajectory Control ◽  
New Method ◽  
Multiple Robots ◽  
Simulation Results ◽  
Articulated Robot ◽  
Neural Optimization

SUMMARYA collision-free trajectory control for multiple robots is proposed. The proposed method is based on the concept of neural optimization network. The positions or configurations of robots are taken as the variables of the neural circuit, and the energy of network is determined by combining various functions, in which one function is to make each robot approach to its goal and another helps each robot from colliding with other robots or obstacles. Also a differential equation of the circuit which tends to minimize the energy is derived. A new method for describing collision between articulated arms is presented and some heuristic method to improve the feasibility and the safety of the trajectory is proposed. Also illustrative simulation results for mobile robots and articulated robot arms are presented.

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 Foraging Task of Multiple Mobile Robots in a Dynamic Environment Using Adaptive Behavior in Crickets

2007 ◽  
Vol 19 (4) ◽  
pp. 466-473 ◽  
Author(s):  
Masatoshi Ashikaga ◽  
◽  
Mika Kikuchi ◽  
Tetsutaro Hiraguchi ◽  
Midori Sakura ◽  
...  
Keyword(s):  
Mobile Robots ◽  
Adaptive Behavior ◽  
Dynamic Environment ◽  
Multiple Mobile Robots ◽  
Fighting Behavior ◽  
Simulation Results ◽  
Foraging Task

In this paper, we propose an algorithm for multiple mobile robots performing a foraging task. In the proposed algorithm, robots select behaviors based on their activities, which were adjusted by interaction with other robots and foods. The proposed algorithm was inspired by the mechanism governing the fighting behavior in male crickets. Simulation results showed that the algorithm is efficient in a dynamic environment.

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.

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