Coordinating mobile robot group behavior using a model of interaction dynamics

1999 ◽  
Author(s):  
Dani Goldberg ◽  
Maja J. Matarić
Keyword(s):  
Mobile Robot ◽  
Group Behavior ◽  
Interaction Dynamics ◽  
Robot Group

Control of mobile robot group using collaborative drone

2019 ◽  
Vol 7 (3) ◽  
pp. 208-214
Author(s):  
Stanislav Zenkevich ◽  
Anaid Nazarova ◽  
Jianwen Huo
Keyword(s):  
Mobile Robot ◽  
Robot Group

Control System of Mobile Robot Group

2014 ◽  
pp. 3-18
Author(s):  
Artur Babiarz ◽  
Radosław Zawiski ◽  
Michał Skrzypek ◽  
Aleksander M. Nawrat
Keyword(s):  
Control System ◽  
Mobile Robot ◽  
Robot Group

scholarly journals Practical Design and Use of Transfer System by Autonomous Mobile Robot Group

2010 ◽  
Vol 28 (3) ◽  
pp. 311-318 ◽  
Author(s):  
Ryosuke Murai ◽  
Tatsuo Sakai ◽  
Hiroyuki Uematsu ◽  
Hisato Nakajima ◽  
Koichi Mitani ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Transfer System ◽  
Autonomous Mobile Robot ◽  
Practical Design ◽  
Robot Group

Human-robot interface system with robot group control for multiple mobile robot systems

1998 ◽  
pp. 633-644
Author(s):  
José Beltrán Escavy ◽  
Tamio Arai ◽  
Akio Nakamura ◽  
Shinjiro Kakita ◽  
Jun Ota
Keyword(s):  
Mobile Robot ◽  
Interface System ◽  
Group Control ◽  
Robot Systems ◽  
Robot Group

The Effect of Mobile Robot on Group Behavior of Animal

2012 ◽  
Vol 24 (6) ◽  
pp. 1071-1079 ◽  
Author(s):  
Daisuke Fujiwara ◽  
◽  
Kojiro Iizuka ◽  
Yoshiyuki Matsumura ◽  
Tohru Moriyama ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Experimental Analysis ◽  
Group Behavior ◽  
Experimental Results ◽  
Fourth Experiment

This paper observes the effect of a mobile robot on the group behavior of soldier crabs. The mobile robot interacts with eight soldier crabs. For the experimental analysis, this paper adopts four settings. In the first setting, eight soldier crabs are placed in an experiment area without the presence of the robot. In the second, third, and fourth settings, eight soldier crabs are placed in an experiment area with, respectively, a stationary robot, a continuously moving robot, and an intermittently moving robot. These experimental results are analyzed using a fluctuation index. From analysis, it was found that the fluctuation slope for the fourth experiment alone differs from that for other experiments. This result suggests that the intermittently moving robot influences the group behavior of soldier crabs.

scholarly journals A Macroscopic Analytical Model of Collaboration in Distributed Robotic Systems

2001 ◽  
Vol 7 (4) ◽  
pp. 375-393 ◽  
Author(s):  
Kristina Lerman ◽  
Aram Galstyan ◽  
Alcherio Martinoli ◽  
Auke Ijspeert
Keyword(s):  
Analytical Model ◽  
Group Size ◽  
Autonomous Robots ◽  
Group Behavior ◽  
Macroscopic Model ◽  
Computational Time ◽  
Size Analysis ◽  
Computationally Efficient ◽  
Existence Of Optimal Control ◽  
Robot Group

In this article, we present a macroscopic analytical model of collaboration in a group of reactive robots. The model consists of a series of coupled differential equations that describe the dynamics of group behavior. After presenting the general model, we analyze in detail a case study of collaboration, the stick-pulling experiment, studied experimentally and in simulation by Ijspeert et al. [Autonomous Robots, 11, 149–171]. The robots' task is to pull sticks out of their holes, and it can be successfully achieved only through the collaboration of two robots. There is no explicit communication or coordination between the robots. Unlike microscopic simulations (sensor-based or using a probabilistic numerical model), in which computational time scales with the robot group size, the macroscopic model is computationally efficient, because its solutions are independent of robot group size. Analysis reproduces several qualitative conclusions of Ijspeert et al.: namely, the different dynamical regimes for different values of the ratio of robots to sticks, the existence of optimal control parameters that maximize system performance as a function of group size, and the transition from superlinear to sublinear performance as the number of robots is increased.

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