Cellular ants: A method to create collision free trajectories for a cooperative robot team

Ioannidis, Konstantinos; Andreadis, Ioannis

doi:10.1016/j.robot.2010.10.004

Cited by 53 publications

(28 citation statements)

References 27 publications

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“…In [2], authors developed a path planner mechanism which is composed of Cellular Automata (CA) and Ant Colony Optimization (ACO) methods for multiple mobile robots. The proposed method is applicable in a dynamic environment and in real time applications.…”

Section: Related Workmentioning

confidence: 99%

Development of efficient obstacle avoidance and line following mobile robot with the integration of fuzzy logic system in static and dynamic environments

Almasri

Elleithy

Alajlan

2016

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT)

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Section: Related Workmentioning

confidence: 99%

Development of efficient obstacle avoidance and line following mobile robot with the integration of fuzzy logic system in static and dynamic environments

Almasri

Elleithy

Alajlan

2016

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT)

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“…Where, l is the length of quad-rotor's blades; 1 U is the sum of the thrust generated by each rotor; 2 U is rolling moment; 3 U is pitching moment; 4 U is yawing moment.  , , respectively are roll angle, pitch angle, yaw angle.…”

Section: B the Flight Controllermentioning

confidence: 99%

“…Since the world's first cellular robotic system based on multi robot appeared at 1980s, cellular robotic systems have made great progress both in theory and practical applications [2][3][4][5]. With the development of robotic technology and expansion of application fields, marsupial robotic system has attracted great attention [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Design of a heterogeneous marsupial robotic system composed of an USV and an UAV

Fan

Wang

et al. 2016

2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)

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This paper provides both the core ideas of a heterogeneous marsupial robotic System and the details of the practical aspects related to its hardware architecture and cooperative system structure. This heterogeneous marsupial robotic system is composed by an unmanned surface vehicle (USV) that acts as a carrier and an unmanned aerial vehicle (UAV) that acts as a passenger, and it is designed for military tasks and other tasks like environmental monitoring, wild life tracking, and search & rescue missions. Through the combination, the cooperative marsupial robots benefit from their heterogeneity by using the superiority of each team member and overcoming their limitations. Moreover, the attitude control simulation model of the UAV is built, and the self-adaptive fuzzy parameter tuning rules for PID flight controller are given, so as to realize the online self-tuning of the controller parameters. Simulation results show that: compared with the conventional PID controller, this attitude control algorithm of fuzzy selfadaptive PID has a better dynamic response performance.

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“…Marco et al proposed an approach combining the artificial bee colony algorithm and the evolutionary programming algorithm to solve the mobile robot path planning problem [13]. Ant colony algorithm is frequently used to solve various kinds of optimization problems, including mobile robots path planning [14][15][16]. But ant colony algorithm has the local minimum and slow convergence problems.…”

Section: Introductionmentioning

confidence: 99%

Mobile Robot Path Planning Using Ant Colony Algorithm

Zhang¹,

Chen²,

Liu³

2016

IJCA

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Cellular ants: A method to create collision free trajectories for a cooperative robot team

Cited by 53 publications

References 27 publications

Development of efficient obstacle avoidance and line following mobile robot with the integration of fuzzy logic system in static and dynamic environments

Development of efficient obstacle avoidance and line following mobile robot with the integration of fuzzy logic system in static and dynamic environments

Design of a heterogeneous marsupial robotic system composed of an USV and an UAV

Mobile Robot Path Planning Using Ant Colony Algorithm

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