Cooperative exploration based on supervisory control of multi-robot systems

Dai, Xuefeng; Jiang, Laihao; Zhao, Yan

doi:10.1007/s10489-015-0741-3

Cited by 36 publications

(15 citation statements)

References 26 publications

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“…Many multi-robot systems have been proposed to solve a broader set of complex cooperative tasks [5]. The multi-robot system has employed Unmanned Ground Vehicles (UGVs) to achieve the treasure hunt [9] and exploration [10]. Combining multi-robot systems with WSNs can improve the real-time performance of multi-robot systems.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Network Topology Control of Branch-Trimming Robot for Transmission Lines

Wang

Fan

et al. 2019

Electronics

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With the development of engineering technology, the distributed design-based Branch-Trimming Robot (BTR) has been used to ensure the power supply security of transmission lines. However, it remains difficult to combine distributed BTRs with a wireless sensor network to build an efficient multi-robot system. To achieve this combination, a dynamic network topology control method was proposed, combining the motion characteristics of robots with the structure of a distributed wireless sensor network. In addition, a topology-updating mechanism based on node signal strength was adopted as well. To achieve efficient data transmission for distributed multi-robot systems, the present study focused on the design of a distributed network model and a dynamic network topology control strategy. Several simulation and test scenarios were implemented, and the changes of network performance under different parameters were studied. Furthermore, the real scene-based dynamic topology control method considers the relationship between network performance and antenna layout.

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Section: Related Workmentioning

confidence: 99%

Dynamic Network Topology Control of Branch-Trimming Robot for Transmission Lines

Wang

Fan

et al. 2019

Electronics

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“…It also responsible for generation of the map using the collected information. This architecture is working fast for small number of robots and becomes inefficient for large number of robots due to higher communication overhead, and produces a highly vulnerable system if the central control robot malfunctions [10,[14][15][16]. iii.…”

Section: Figure 1 An Example Of Simple Navigation Taskmentioning

confidence: 99%

An Evaluation of Multi-Robot Systems Exploration Algorithms

Mohamed

Elshenawy

Harb

2019

Journal of Al-Azhar University Engineering Sector

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Multi-robot systems exploration of an environment is an important process that most automated applications depend on. In this paper, common algorithms used to perform the exploration process of an unknown cell-based environment occupied by a set of obstacles using a set of identical robots are studied and their performance are compared depending on three metrics: the total explored area in the map, overall mission time, and the number of hops in the networked robots. The performance of these algorithms is evaluated for different environments and different team sizes using MRESim computer simulator.

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“…Solving (25) results in the stationary points Where: x ss , y ss , z ss , ψ ss ∈ R, we notice ss to mean steady state.…”

Section: Non-conserved Torquesmentioning

confidence: 99%

“…For the reasons that the quadrotor system is non-linear and some outputs (x and y) cannot be directly controlled (they are underactuated), we cannot tune the PID parameters with one of classical approaches. Different methods can be used to obtain optimal control of robots [25], [26] in particular, optimal parameters of the PID, among them; we can find meta-heuristic techniques of optimization such as DE [27], PSO [28] and GA [27], [29] which were used in to solve some specific problems. We propose in this work, to use GA as an optimization technique to obtain the best PID's parameters.…”

Section: Genetic Algorithmmentioning

confidence: 99%

Decentralized PID Control by Using GA Optimization Applied to a Quadrotor

Hasseni¹,

Abdou²

2018

JAMRIS

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Quadrotors represent an effective class of aerial robots because of their abilities to work in small areas. We suggested in this research paper to develop an algorithm to control a quadrotor, which is a nonlinear MIMO system and strongly coupled, by a linear control technique (PID), while the parameters are tuned by the Genetic Algorithm (GA). The suggested technique allows a decentralized control by decoupling the linked interactions to effect angles on both altitude and translation position. Moreover, the using a meta-heuristic technique enables a certain ability of the system controllers design without being limited by working on just the small angles and stabilizing just the full actuated subsystem. The simulations were implemented in MATLAB/Simulink tool to evaluate the control technique in terms of dynamic performance and stability. Although the controllers design (PID) is simple, it shows the effect of the proposed technique in terms of tracking errors and stability, even with large angles, subsequently, high velocity response and high dynamic performances with practically acceptable rotors speed.

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Cooperative exploration based on supervisory control of multi-robot systems

Cited by 36 publications

References 26 publications

Dynamic Network Topology Control of Branch-Trimming Robot for Transmission Lines

Dynamic Network Topology Control of Branch-Trimming Robot for Transmission Lines

An Evaluation of Multi-Robot Systems Exploration Algorithms

Decentralized PID Control by Using GA Optimization Applied to a Quadrotor

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