Mohammadreza Asghari Oskoei

Work place: Allameh Tabataba’i University, Tehran, Iran



Research Interests: Computer systems and computational processes, Artificial Intelligence, Computer Vision, Robotics


Mohammadreza Asghari Oskoei is a Professor Assistant in University of Allameh Tabataba’i (Iran) and Visiting Researcher in University of Essex (UK). He is a member of Human Centred Robotics Group in University of Essex. He received his MSc in Control System Engineering from the University of Tehran (Iran) in 1993 and his PhD in Computer Science from the University of Essex in 2009. He was member of EU research project (LIREC - Living with Robots and interactive Companions) in University of Hertfordshire, UK (2009-2012). His research interests include Artificial Intelligence, Computer Vision and Robotics.

Author Articles
Mobile Robot Path Planning by RRT* in Dynamic Environments

By Roudabe Seif Mohammadreza Asghari Oskoei

DOI:, Pub. Date: 8 Apr. 2015

Robot navigation is challenging for mobile robots technology in environments with maps. Since finding an optimal path for the agent is complicated and time consuming, path planning in robot navigation is an axial issue. The objective of this paper is to find a reasonable relation between parameters used in the path planning algorithm in a platform which a robot will be able to move from the start point in a dynamic environment with map and plan an optimal path to specified goal without any collision with moving and static obstacles. For this purpose, an asymptotically optimal version of Rapidly-exploring Random Tree RRT algorithm, named RRT* is used. The algorithm is based on an incremental sampling which covers the whole space and acts fast. Moreover this algorithm is computationally efficient, therefore it can be used in multidimensional environments. The obtained results indicate that a feasible path for mobile holomonic robot may be found in a short time by using this algorithm. Also different standard distances measurements like (Chebyshev, Euclidean, and City Block) are examined, and coordinated with sampling node number in order to reach the suitable result based on environment circumstances.

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