Formation Control of Multiple Behavior-based robots

Liu, Bailong; Zhang, Rubo; Shi, Changting

doi:10.1109/iccias.2006.294194

Cited by 19 publications

(7 citation statements)

References 4 publications

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“…This system consists of acoustic micro-modem to transmit data between vehicles and to provide Long Base-Line (LBL) positioning information, rack-mount PC to run control software, GPS receiver card and attitude sensor to provide time and position information and provide heading and depth respectively. Furthermore, Liu et al (2006) controlled the formation of a group of AmigoBot robots using behavioral motor schema-based architecture. The robots shared information using a wireless network based on UDP protocol connected to a remote PC with a wireless adaptor sharing information between the leader and the followers.…”

Section: State Of Artmentioning

confidence: 99%

Development of a hybrid multi-layer control architecture for a cooperative team ofN− homogeneous robots

ElAshry

Ramadan

ElAlaily

et al. 2019

Transactions of the Institute of Measurement and Control

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This paper proposes a hybrid centralized control architecture for formation control of N-homogeneous mobile robots. The addressed problem is maintaining an equilateral triangular formation using three mobile robots while moving towards a desired target avoiding any collision. The proposed architecture is divided into four main subsystems; a main path-planner, a nonlinear Lyapunov-based controller, a Secure Shell (SSH) communication module and an image processing algorithm. The main path-planner subsystem itself is subdivided into three algorithms; brain-like algorithm, sub-path-planner and an information center algorithm. The brain-like algorithm is responsible for all the decision making. On the other hand, the sub-path-planner works on translating the decisions of the brain into more precise decisions to the individual robots. Meanwhile, the information center acts as the memory for the brain to access saved information previously shared between the robots. It is shown that the control algorithm allows any initial allocation of the three robots to converge to a triangle formation in an optimal manner while avoiding collisions. Finally, the potential use of this formation as a platform acting as an autonomous mobile helipad is introduced as a practical application for the proposed architecture.

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Section: State Of Artmentioning

confidence: 99%

Development of a hybrid multi-layer control architecture for a cooperative team ofN− homogeneous robots

ElAshry

Ramadan

ElAlaily

et al. 2019

Transactions of the Institute of Measurement and Control

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show abstract

“…The behavior-based method [ 10 , 11 , 12 ] integrates the various goal-oriented behaviors and each robot decides how to accomplish its own goal. In this method, each robot assigns a relatively high priority to behaviors that are more important for accomplishing its goal, and integrates the behaviors according to its priorities.…”

Section: Related Researchmentioning

confidence: 99%

Middleware Design for Swarm-Driving Robots Accompanying Humans

Kim

Kang

2017

Sensors

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Abstract:Research on robots that accompany humans is being continuously studied. The Pet-Bot provides walking-assistance and object-carrying services without any specific controls through interaction between the robot and the human in real time. However, with Pet-Bot, there is a limit to the number of robots a user can use. If this limit is overcome, the Pet-Bot can provide services in more areas. Therefore, in this study, we propose a swarm-driving middleware design adopting the concept of a swarm, which provides effective parallel movement to allow multiple human-accompanying robots to accomplish a common purpose. The functions of middleware divide into three parts: a sequence manager for swarm process, a messaging manager, and a relative-location identification manager. This middleware processes the sequence of swarm-process of robots in the swarm through message exchanging using radio frequency (RF) communication of an IEEE 802.15.4 MAC protocol and manages an infrared (IR) communication module identifying relative location with IR signal strength. The swarm in this study is composed of the master interacting with the user and the slaves having no interaction with the user. This composition is intended to control the overall swarm in synchronization with the user activity, which is difficult to predict. We evaluate the accuracy of the relative-location estimation using IR communication, the response time of the slaves to a change in user activity, and the time to organize a network according to the number of slaves.

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“…In the centralized structure the leader of the formation is responsible for getting all the information relative to all the robots in the team, such as the relative poses, and for sending the suitable control signals to each one, in order to establish the desired formation [10]. On the other hand, if a decentralized structure is adopted, such a unit centralizing the information is not necessary anymore: each robot in the formation has its own sensors to get the information about its pose, the state of the environment surrounding it, the poses of the other robots (normally related to its system of coordinates) and, by itself, generates control signals it needs to reach its desired pose in order to get the formation [2].…”

Section: Introductionmentioning

confidence: 99%

“…For the behavioral approach, a set of procedures is defined for each robot in the team, such as to seek for the goal, to avoid obstacles and to establish the formation. The control signals sent to each individual robot in the platoon correspond, in general, to a weighted mean determined by considering all the available behaviors [8] [9] [10].…”

Section: Introductionmentioning

confidence: 99%

Decentralized control of leader-follower formations of mobile robots with obstacle avoidance

Brandão

Sarcinelli-Filho

Carelli

et al. 2009

2009 IEEE International Conference on Mechatronics

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Ab8tract~This paper proposes a decentralized control scheme to guide a leader-follower formation of unicycle-like mobile robots to pass between static obstacles, demanding just one controller per robot. Two approaches are discussed, in terms of obstacle avoidance. One considers the whole formation as a virtual robot, which should avoid obstacles and keep the formation aspect. To do that, the leader robot takes care of goal seeking and obstacle avoidance, while the follower one just keeps the formation as a whole rigid body (rigid formation). In the second approach, the follower robot keeps only its separation from the leader (semirigid formation) and avoids obstacles, while the leader one seeks for the goal and avoids obstacles. In each case, the controllers onboard the robots do not share information during navigation (the control strategy is a decentralized one). Experimental results validating the proposal are also presented and discussed.

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Formation Control of Multiple Behavior-based robots

Cited by 19 publications

References 4 publications

Development of a hybrid multi-layer control architecture for a cooperative team ofN− homogeneous robots

Development of a hybrid multi-layer control architecture for a cooperative team ofN− homogeneous robots

Middleware Design for Swarm-Driving Robots Accompanying Humans

Decentralized control of leader-follower formations of mobile robots with obstacle avoidance

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