Experimental Evaluation of a Tele-Operated Robot System in Traversing a Narrow Path
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Abstract:
Tele-operated robot systems are expected to greatly assist humans in dangerous environments, such as natural disaster sites. Thus, we have developed a mobile robot system that is tele-operated via the Internet from any location and is capable of traversing narrow paths. Herein, we developed a control algorithm for traversing a narrow path and experimentally verified the ability of the robot iws09 which was 370 mm in diameter, to automatically pass through a narrow path having a clearance of 40 mm on both sides without collisions. Furthermore, the wheel-driving characteristics of the robot were verified. The function of traversing a narrow path will be helpful to support an operator remotely controlling the robot. Next, we will develop a mobile robot control system to cope with other situations.Keywords:
Traverse
Telerobotics
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Mobile robots are slowly growing in number and complexity due to their applications. A mobile robot needs locomotion mechanisms that enable it to move unbounded throughout its environment. Navigation of robot in a dynamic environment is a complicated issue due to the fact that a variety of obstacles has to be detected and a collision free path must be chosen. For an autonomous robot, obstacle detection and path planning are crucial tasks for the success of the robot. In this work an image based obstacle detection and path planning system is proposed. The basic idea is to implement path planning by considering the spacing between the obstacles and comparing with a predefined threshold to estimate whether it is a traversable path.
Obstacle avoidance
Mobile Robot Navigation
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Any-angle path planning
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The potential field method is widely used for autonomous mobile robot path planning. However, most potential field methods are designed to be applied in the stationary environment. In this paper, an improved potential field method is proposed for automatic mobile robot path planning in a dynamic environment. Improved method takes the position, the velocity, the acceleration and the physical size of the robot into account, and the relative factor of the distance and the acceleration is introduced in the potential function. The simulation result proves the effectiveness of this method.
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