Humanoid robot path planning with fuzzy Markov decision processes

Fakoor, Mahdi; Kosari, Amirreza; Jafarzadeh, Mohsen

doi:10.1016/j.jart.2016.06.006

Cited by 70 publications

(41 citation statements)

References 15 publications

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“…Bayesian methods uses the same iterative prediction-update process than in the Kalman filter, but they do not rely on its restrictive assumptions [52]. The pros are that they can use nonlinear models for both trajectory planning and sensing and an arbitrary distribution instead of a Gaussian.…”

Section: Decision-making Process Techniques For Trajectory Planningmentioning

confidence: 99%

Optimization approaches for robot trajectory planning

Llopis-Albert

Rubio

2018

Mult.J.Edu.Soc.Tec.Sci.

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The development of optimal trajectory planning algorithms for autonomous robots is a key issue in order to efficiently perform the robot tasks. This problem is hampered by the complex environment regarding the kinematics and dynamics of robots with several arms and/or degrees of freedom (dof), the design of collision-free trajectories and the physical limitations of the robots. This paper presents a review about the existing robot motion planning techniques and discusses their pros and cons regarding completeness, optimality, efficiency, accuracy, smoothness, stability, safety and scalability.

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Section: Decision-making Process Techniques For Trajectory Planningmentioning

confidence: 99%

Optimization approaches for robot trajectory planning

Llopis-Albert

Rubio

2018

Mult.J.Edu.Soc.Tec.Sci.

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“…The autonomous path planning ensures that the robot can work effectively in real world applications. They have used humanoid robot (NAO H25 V4) to implement and develop the method successfully …”

Section: Literature Reviewmentioning

confidence: 99%

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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“…The range of topics in the publications on this subject is very wide. They examine problems on making fuzzy decisions in the Markov systems [16], the problems of fuzzy control in such systems [17], etc. In all cases, correctness of the result is defined by the level of substantiation of the adopted technology for calculating the stationary probability distributions for the fuzzy Markov systems.…”

Section: Finding the Probability Distribution Of States In The Fuzzy mentioning

confidence: 99%

Finding the probability distribution of states in the fuzzy markov systems

Раскін

Сіра

Katkova

2017

EEJET

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Розв'язана задача відшукання стаціонарних розподілів ймовірностей станів для марковських систем в умовах невизначеності. Передбачається, що параметри аналізованих систем задані нечіт-ко. У задачі аналізу напівмарковських системи оцінка компонентів стаціонарного розподілу ймо-вірностей станів системи отримана шляхом міні-мізації комплексного критерію. Критерій враховує міру відхилення шуканого розподілу від модально-го, а також рівень компактності функції прина-лежності нечіткого результату рішення Ключові слова: марковська і напівмарков-ська системи, комплексний критерій, відхилен-ня рішення від модального, міра компактності рішення Решена задача отыскания стационарных рас-пределений вероятностей состояний для мар-ковских систем в условиях неопределенности. Предполагается, что параметры анализируемых систем заданы нечетко. В задаче анализа полу-марковской системы оценка компонентов стаци-онарного распределения вероятностей состояний системы получена путем минимизации комплекс-ного критерия. Критерий учитывает меру откло-нения искомого распределения от модального, а также уровень компактности функции принад-лежности нечеткого результата решения Ключевые слова: марковская и полумарков-ская системы, комплексный критерий, отклоне-ние решения от модального, мера компактности решения UDC 519.2

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Humanoid robot path planning with fuzzy Markov decision processes

Cited by 70 publications

References 15 publications

Optimization approaches for robot trajectory planning

Optimization approaches for robot trajectory planning

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

Finding the probability distribution of states in the fuzzy markov systems

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