Path planning of a group of robots with potential field approach: decentralized architecture

Matoui, Fethi; Boussaid, Boumedyen; Metoui, Brahim; Frej, Ghazi Bel Haj; Abdelkrim, Mohamed Naceur

doi:10.1016/j.ifacol.2017.08.1822

Cited by 17 publications

(11 citation statements)

References 4 publications

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“…The profile is presented in Figure 21. The formulas used to determine the repulsive forces are given in Equations (25) and (30). The repulsive forces are zero if the trajectory of the robot does not carry a risk of collision with the static obstacles or with the others robots.…”

Section: Simulation Resultsmentioning

confidence: 99%

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Distributed path planning of a multi-robot system based on the neighborhood artificial potential field approach

2018

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The current study is set up to investigate the problem of planning the trajectories of a multi-robot system. It puts emphasis on the idea of using distributed architecture to plan the trajectories of a group of wheeled mobile robots. Each robot must be able to detect and avoid collision with both static and dynamic obstacles present in its environment/neighborhood. This study seeks to improve the artificial potential field (APF) method in order to have good trajectory planning of a multi-robot system. In order to address the purpose of this work, we employed the hybrid approach, which is a combination of three techniques: the APF method; the neighborhood system; and the notion of priority between the robots. Moreover, the minimum local problem is handled in this paper using the non-minimum speed algorithm. The implemented approach is adapted to solve the trajectory planning problem for a multi-robot system. So, the problem of intersection of robots at the same passage point is solved through using the method of assignment of priority between robots. We also used the neighborhood detection technique to reduce the influence area of each robot and to optimize the time of calculation. The overall system equations associated to the robots are updated at each time of simulation to react at any condition that might suddenly emerge. The approach is implemented with MATLAB/Simulink and Solidworks/Simmechanics.

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Section: Simulation Resultsmentioning

confidence: 99%

“…In our paper, we use the robot ''Pioneer 3DX'' modeled by Solidworks. 30 Pioneer 3DX is a wheeled mobile robot built by Adept Mobile Robots. In this section, we first focus on identifying its kinematic model and its dynamic model.…”

Section: Wheeled Mobile Robot Modelingmentioning

confidence: 99%

Distributed path planning of a multi-robot system based on the neighborhood artificial potential field approach

2018

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“…From managerial insights, Sarkar et al have focused on increasing the safety factors and reducing the setting time [9]. Some well-known path-planning techniques like A * [10,11], Dijkstra [12], distance conversion [13,14], potential field [15][16][17][18][19], sampling-based [20,21], and piano stimulation problem [22][23][24] need more information and sometimes they require a full map. This weakness shows that in unknown environments, point-to-point guidance is necessary.…”

Section: Introductionmentioning

confidence: 99%

“…The robot path planning using the artificial potential field procedure is one of the most popular path planning methods. By implementing the artificial potential field method, Matoui et al proposed a path planning algorithm to push the robots far from the danger space in unknown environment [18].…”

Section: Introductionmentioning

confidence: 99%

Robot Motion Planning in an Unknown Environment with Danger Space

et al. 2019

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This paper discusses the real-time optimal path planning of autonomous humanoid robots in unknown environments regarding the absence and presence of the danger space. The danger is defined as an environment which is not an obstacle nor free space and robot are permitted to cross when no free space options are available. In other words, the danger can be defined as the potentially risky areas of the map. For example, mud pits in a wooded area and greasy floor in a factory can be considered as a danger. The synthetic potential field, linguistic method, and Markov decision processes are methods which have been reviewed for path planning in a free-danger unknown environment. The modified Markov decision processes based on the Takagi–Sugeno fuzzy inference system is implemented to reach the target in the presence and absence of the danger space. In the proposed method, the reward function has been calculated without the exact estimation of the distance and shape of the obstacles. Unlike other existing path planning algorithms, the proposed methods can work with noisy data. Additionally, the entire motion planning procedure is fully autonomous. This feature makes the robot able to work in a real situation. The discussed methods ensure the collision avoidance and convergence to the target in an optimal and safe path. An Aldebaran humanoid robot, NAO H25, has been selected to verify the presented methods. The proposed methods require only vision data which can be obtained by only one camera. The experimental results demonstrate the efficiency of the proposed methods.

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“…The path planning methods shown in the previous literature are divided into two major approaches: classical approach as well as heuristic approach (utilizing Artificial Intelligence Technique) [13]. Prominent classical planning approaches comprise the Potential Field Method [14], Probabilistic Roadmap (PRM) [15], Grid Based Method [16], Rapidly Exploring Random Tree [17] and. heuristic planning approaches involve fuzzy logic [18], artificial neural network [19], ant colony algorithm [20], genetic algorithm (GA) optimization [21] and the approaches based on particle swarm optimization [22].…”

Section: Introductionmentioning

confidence: 99%

A Novel Path Planning System for Guidance of Blind People using Integration of GA and A* Techniques

Mohamed¹,

E.²,

F.³

2019

IJCA

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It is a challenging task for the blind people to perceive indoor environment information and walk independently. Path planning is a crucial requirement to provide constant assistance for blind people to navigate from one location to another. This paper presents a novel system for path planning to assist blind people for walking through the indoor environment and avoiding the obstacles. The algorithm is based on genetic algorithm and A* algorithm to select the shortest path that achieves the lowest computational time. A comparison a mong the GA, A* and the new algorithm shows that is faster and shorter than the previous algorithms.

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Path planning of a group of robots with potential field approach: decentralized architecture

Cited by 17 publications

References 4 publications

Distributed path planning of a multi-robot system based on the neighborhood artificial potential field approach

Distributed path planning of a multi-robot system based on the neighborhood artificial potential field approach

Robot Motion Planning in an Unknown Environment with Danger Space

A Novel Path Planning System for Guidance of Blind People using Integration of GA and A* Techniques

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