Mobile Multi-Robot Control in Target Search and Retrieval

2008 ◽  
Author(s):  
Guoxian Zhang ◽  
Devendra P. Garg
Keyword(s):  
Task Performance ◽  
Robot Control ◽  
Swarm Robotics ◽  
Retrieval System ◽  
Robot System ◽  
Target Search ◽  
Transition Mechanism ◽  
Environment Exploration ◽  
Search And Retrieval ◽  
Multi Robot

In this paper, the design of a controller is proposed for a multi-robot target search and retrieval system. Inspired by research in insect foraging and swarm robotics, we developed a transition mechanism for the multi-robot system. Environmental information and task performance obtained by the robot system are used to adjust individual robot’s parameters and guide environment exploration. The proposed control system is applicable in the solution of multi-target problem also where several robots may be needed to cooperate together to retrieve a large target. Simulations show that the task performance improves significantly with the proposed method by sharing information in parameter learning and environment exploration.

scholarly journals Self-Organization of Multi-Robot System Based on External Stimuli

2019 ◽  
Vol 15 (2) ◽  
pp. 101-114
Author(s):  
Yousif Kheerallah ◽  
Ali Marhoon ◽  
Mofeed Rashid ◽  
Abdulmuttalib Rashid
Keyword(s):  
Robot Control ◽  
Light Spot ◽  
Self Organization ◽  
Robot System ◽  
Straight Line ◽  
Individual System ◽  
External Stimuli ◽  
The Mathematical Model ◽  
High Intensity Light ◽  
Multi Robot

In modern robotic field, many challenges have been appeared, especially in case of a multi-robot system that used to achieve tasks. The challenges are due to the complexity of the multi-robot system, which make the modeling of such system more difficult. The groups of animals in real world are an inspiration for modeling of a multi-individual system such as aggregation of Artemia. Therefore, in this paper, the multi-robot control system based on external stimuli such as light has been proposed, in which the feature of tracking Artemia to the light has been employed for this purpose. The mathematical model of the proposed design is derived and then Simulated by V-rep software. Several experiments are implemented in order to evaluate the proposed design, which is divided into two scenarios. The first scenario includes simulation of the system in situation of attraction of robot to fixed light spot, while the second scenario is the simulation of the system in the situation of the robots tracking of the movable light spot and formed different patterns like a straight-line, circular, and zigzag patterns. The results of experiments appeared that the mobile robot attraction to high-intensity light, in addition, the multi-robot system can be controlled by external stimuli. Finally, the performance of the proposed system has been analyzed.

Efficiency Assessment of Performance of Decentralized Autonomous Multi-Robot Systems

1996 ◽  
Vol 8 (3) ◽  
pp. 286-291 ◽  
Author(s):  
Arvin Agah ◽  
◽  
George A. Bekey ◽  
◽  
Keyword(s):  
Task Performance ◽  
Virtual World ◽  
Energy Requirement ◽  
Robot System ◽  
Efficiency Assessment ◽  
The World ◽  
Robot Systems ◽  
Time Required ◽  
And Control ◽  
Multi Robot

This paper presents a new methodology for the efficiency assessment of task performance of decentralized autonomous multi-robot system. This formulation considers the types of the robots (in terms of sensing, action, and control), the description of the environment (the world), the facts (rules) of the world, and the specifications of the tasks to be performed. The performance efficiency is defined in terms of the total time required for completing the task, total energy requirement, and the comparison of the final results and the desired results. A robot colony simulator was used to perform a number of experiments, measuring the task performance efficiency, of a colony of simulated robots which perform specific tasks in a virtual world. The experimental results are presented in this paper. This paper also describes a team of four robots designed and fabricated in hardware. The physical robots were used successfully to validate the results from the simulated colony.

Exploration Strategies of Coordinated Multi-Robot System: A Comparative Study

2018 ◽  
Vol 7 (1) ◽  
pp. 48
Author(s):  
Ayman. El shenawy ◽  
Khalil. Mohamed ◽  
Hany. M. Harb
Keyword(s):  
Comparative Study ◽  
Process Performance ◽  
Basic Process ◽  
Robot System ◽  
Exploration Process ◽  
Coordination Strategy ◽  
System A ◽  
Environment Exploration ◽  
Robot Systems ◽  
Multi Robot

Environment Exploration is the basic process that most of Multi Robot Systems applications depend on it. The exploration process performance depends on the coordination strategy between the robots participating in the team.  In this paper the coordination of Multi Robot Systems in the exploration process is surveyed, and the performance of different Multi Robot Systems exploration strategies is contrasted and analyzed for different environments and different team sizes.

scholarly journals An emotional model for swarm robotics

2019 ◽  
Vol 22 (3) ◽  
Author(s):  
Angel Gil ◽  
Eduardo Puerto ◽  
Jose Aguilar ◽  
Eladio Dapena
Keyword(s):  
Swarm Robotics ◽  
Recognition Algorithm ◽  
Emergent Behavior ◽  
Robot System ◽  
Level Of Satisfaction ◽  
Emotional Model ◽  
Object Transportation ◽  
The Individual ◽  
Emergent Behaviors ◽  
Multi Robot

Swarm robotics is a system of multiple robots where a desired collective behavior emerges from the interactions between the robots and with the environment. This paper proposes an emotional model for the robots, to allow emerging behaviors. The emotional model uses four universal emotions: anger, disgust, sadness, and joy, assigned to each robot based on the level of satisfaction of its basic needs. These emotions lie on a spectrum where depending where the emotion of the robot lies, can affect its behavior and of its neighboring robots. The more negative the emotion is, the more individualistic it becomes in its decisions. The more positive the robot is in its emotion, the more it will consider the group and global goals. Each robot is able to recognize another robot's emotion in the system based on their current state, using the AR2P recognition algorithm. Specifically, the paper addresses emotions’ influence on the behavior of the system, at the individual and collective levels, and the emotions’ effects on the emergent behaviors of the multi-robot system. The paper analyses two emergent scenarios: nectar harvesting and object transportation, and shows the importance of the emotions into the emergent behavior in a multi-robot system

scholarly journals Reinforcement-Learning-Based Asynchronous Formation Control Scheme for Multiple Unmanned Surface Vehicles

2021 ◽  
Vol 11 (2) ◽  
pp. 546
Author(s):  
Jiajia Xie ◽  
Rui Zhou ◽  
Yuan Liu ◽  
Jun Luo ◽  
Shaorong Xie ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Formation Control ◽  
Rapid Development ◽  
Gradient Algorithm ◽  
Robot System ◽  
Physical Relationship ◽  
Unmanned Surface Vehicles ◽  
Main Challenge ◽  
Control Scheme ◽  
Multi Robot

The high performance and efficiency of multiple unmanned surface vehicles (multi-USV) promote the further civilian and military applications of coordinated USV. As the basis of multiple USVs’ cooperative work, considerable attention has been spent on developing the decentralized formation control of the USV swarm. Formation control of multiple USV belongs to the geometric problems of a multi-robot system. The main challenge is the way to generate and maintain the formation of a multi-robot system. The rapid development of reinforcement learning provides us with a new solution to deal with these problems. In this paper, we introduce a decentralized structure of the multi-USV system and employ reinforcement learning to deal with the formation control of a multi-USV system in a leader–follower topology. Therefore, we propose an asynchronous decentralized formation control scheme based on reinforcement learning for multiple USVs. First, a simplified USV model is established. Simultaneously, the formation shape model is built to provide formation parameters and to describe the physical relationship between USVs. Second, the advantage deep deterministic policy gradient algorithm (ADDPG) is proposed. Third, formation generation policies and formation maintenance policies based on the ADDPG are proposed to form and maintain the given geometry structure of the team of USVs during movement. Moreover, three new reward functions are designed and utilized to promote policy learning. Finally, various experiments are conducted to validate the performance of the proposed formation control scheme. Simulation results and contrast experiments demonstrate the efficiency and stability of the formation control scheme.

scholarly journals Research Progress on Synergistic Technologies of Agricultural Multi-Robots

2021 ◽  
Vol 11 (4) ◽  
pp. 1448
Author(s):  
Wenju Mao ◽  
Zhijie Liu ◽  
Heng Liu ◽  
Fuzeng Yang ◽  
Meirong Wang
Keyword(s):  
Path Planning ◽  
Formation Control ◽  
Research Progress ◽  
Hybrid Architecture ◽  
Labor Costs ◽  
Robot System ◽  
System Architectures ◽  
Research Results ◽  
Robot Systems ◽  
Multi Robot

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

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