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This paper proposes a novel algorithm for mobile robot navigation in completely unknown dynamic environments involving humans. Unlike existing navigation algorithms that assume full knowledge of the environment, i.e. position, direction and velocity of all obstacles, the proposed algorithm is only based on the local sensory information. The algorithm, inspired from pedestrian studies, has a proxemics-based...
Path planning with obstacles avoidance in dynamic environments is a crucial issue in robotics. Numerous approaches have been suggested for the navigation of mobile robots with moving obstacles. In this paper, about 50 articles have been reviewed and briefly described to offer an outline of the research progress in motion planning of mobile robot approaches in dynamic environments for the last five...
This paper proposes a navigation algorithm that considers the states of humans and robots in order to achieve harmonious coexistence between them. A robot navigation in the presence of humans and other robots is rarely considered in the field of robotics. When navigating through a space filled with humans and robots with different functions, a robot should not only pay attention to obstacle avoidance...
Based on the dynamic window approach (DWA) for robot navigation, this paper presents a local reactive method, called DWA*, for mobile robots to achieve high-speed, smooth, and local-minima-free navigation. The original DWA utilizes only a small part of environmental information to search for a proper motion command in the robot's motion space. Hence, the robot can be easily driven into local-minima...
We propose a novel boundary-following algorithm that works in conjunction with any potential function that is guaranteed to take the robot to the target. The potential field must not have any local minima but is not required to avoid moving too closely to the boundary. The proposed method has several advantages: a) The calculation of the C-space is avoided, which can be costly especially if the robot...
Robot navigation methods can be divided into two classes: global path planning and local reactive methods. Global path planning methods find an optimal path to a specified goal, while local reactive methods compute proper control commands for the robot according to recent sensory information. In this paper, a new navigation method is presented, the new method integrates dynamic window approach (DWA)...
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