Optimal path planning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control

Bakdi, Azzeddine; Hentout, Abdelfetah; Boutami, Hakim; Maoudj, Abderraouf; Hachour, Ouarda; Bouzouia, Brahim

doi:10.1016/j.robot.2016.12.008

Cited by 213 publications

(101 citation statements)

References 39 publications

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“…This robot performed many tasks like modeling and perception of environment around its surroundings; in addition, it finds the best collision‐free path for determining the position and orientation to execute the generated path using genetic algorithm. Addition to that information are collected image processing techniques …”

Section: Literature Reviewmentioning

confidence: 99%

“…Finally, they found that proposed algorithms were very effective to plan the path for robot with limited angular velocities. 23 Bakdi et al 24 proposed and implemented an offline Kinect-based optimal collision-free path planning for a differentially driven indoor mobile robot. This robot performed many tasks like modeling and perception of environment around its surroundings; in addition, it finds the best collision-free path for determining the position and orientation to execute the generated path using genetic algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Addition to that information are collected image processing techniques. 24 Nie et al 25 proposed a non-linear inertia and annealing PSO algorithm to overcome the shortcomings of the basic PSO algorithm, and they are simulated both in simple and complex environments to check the effectiveness of proposed algorithm and it is compared with the basic PSO algorithm. 25 Sheikhattar and Kalantari 26 proposed a distributed load balancing protocol based on ADMM iterations for general network configuration.…”

Section: Literature Reviewmentioning

confidence: 99%

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Establishing an emergency communication network and optimal path using multiple autonomous rover robots

Sakthitharan¹,

Jayashri²

2018

Concurrency and Computation

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Summary The natural calamity or disaster may destroy all communication networks especially a cellular network that relies on a tower. Although many solutions to an ad hoc wireless network have been proposed, forming a network covering a respective region with mobile robots toward optimal coverage remains to be an open problem. In this paper, we take the initiative to handle the optimal network coverage and path selection in disaster region with the help of multiple movable/rover robots. This paper consists of load balance distribution algorithm and optimal coverage algorithm applied to find the next optimally possible node location for all robots. Next, the robots maneuvering in an unknown disaster environment to identify the optimal path between the source and destination by using a particle swarm optimization algorithm. Finally, simulated results show that the algorithms can significantly improve the network coverage in the entire region, and the optimal path can effectively identify the optimal solution for all rover robots.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Establishing an emergency communication network and optimal path using multiple autonomous rover robots

Sakthitharan¹,

Jayashri²

2018

Concurrency and Computation

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“…By defining a combined fitness function, MOGAs can also take various objectives into account at the same time. For instance, the multi-objectives are EE's positioning error and joint displacement for a redundant manipulator 22 and for a mobile manipulator 24 , mobile base and joint's displacements for a mobile manipulator 23 , the navigation length, path-obstacles intersection and accumulated change of mobile base's orientation for a mobile vehicle 25 , etc. However, most of them do not study the coordination between the position-orientation of mobile base and manipulator's configuration, and not mention the "human-like" motion design.…”

Section: Introductionmentioning

confidence: 99%

Motion Planning for a Humanoid Mobile Manipulator System

Yan

Jiang

Rahmani

et al. 2019

Int. J. Human. Robot.

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A high redundant non-holonomic humanoid mobile dual-arm manipulator system (MDAMS) is presented in this paper where the motion planning to realize "humanlike" autonomous navigation and manipulation tasks is studied. Firstly, an improved MaxiMin NSGA-II algorithm, which optimizes five objective functions to solve the problems of singularity, redundancy, and coupling between mobile base and manipulator simultaneously, is proposed to design the optimal pose to manipulate the target object. Then, in order to link the initial pose and that optimal pose, an off-line motion planning algorithm is designed. In detail, an efficient direct-connect bidirectional RRT and gradient descent algorithm is proposed to reduce the sampled nodes largely, and a geometric optimization method is proposed for path pruning. Besides, head forward behaviors are realized by calculating the reasonable orientations and assigning them to the mobile base to improve the quality of human-robot interaction. Thirdly, the extension to online planning is done by introducing real-time sensing, collision-test and control cycles to update robotic motion in dynamic environments. Fourthly, an EEs' via-point-based multi-objective genetic algorithm (MOGA) is proposed to design the "human-like" viaposes by optimizing four objective functions. Finally, numerous simulations are presented to validate the effectiveness of proposed algorithms.

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“…We divide it into singular perturbation method [1] , nonlinear programing method [2] , dynamic programming [3] , genetic algorithm [4] , ant colony algorithm [5] and artificial potential field (APF) [6] etc. The APF converges quickly, but there are objects unreachable, easy to fall into the local optimal, and solve these problems through the improved artificial potential field method.…”

Section: Introductionmentioning

confidence: 99%

3D Path Planning for Multi-UAV Base on Artificial Potential Field Method

Guo¹,

Hu²,

Feng³

2018

dtetr

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Abstract. This paper puts forward the improved artificial potential for UAV path planning. The idea of segmentation planning is used to plan the cruise section and the end with different algorithms, and from a single UAV to multi UAV path planning. According to the angle of the UAV and the threat, the angle between the leader and the wingman and the threat calculated. The angle formula of the leader and the threat is taken as part of the angle of the wingman and the threat. By adjusting the leader and angle of threat and the follower aircraft coefficient. The angle formula of improved the wingman and threat is get. To solve the different starting point of multi UAV formation flying after confluence and reach the target point of the problem at the same time. Simulation results show the effectiveness of the algorithm.

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Optimal path planning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control

Cited by 213 publications

References 39 publications

Establishing an emergency communication network and optimal path using multiple autonomous rover robots

Establishing an emergency communication network and optimal path using multiple autonomous rover robots

Motion Planning for a Humanoid Mobile Manipulator System

3D Path Planning for Multi-UAV Base on Artificial Potential Field Method

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