Local Information using Stereo Camera in Artificial Potential Field based Path Planning

Generally, a robot acquires environment data from the sensor that is attached to the robot itself and merely obtains local information. Artificial Potential Field (APF) is designed as the path planning with global information. Therefore, local information becomes one of the issues in the APF based path planning. This paper proposes an approach to handle the local information in the APF using framework transformation. With integration of image processing, clustering, and framework transformation, the initial, goal, and obstacles from the real world coordinate can be determined in the APF environment scenario. Transformation of the two-dimensional image is used to generate the APF path planning. The local optima in the local information is set as waypoint for the global optimum in whole environment scenario. In order to test performance of the algorithm, local data set is used. Two scenarios are used in this research, i.e. static environment and dynamic environment with a moving obstacle. The results show that the proposed method can be applied in the real time implementation.

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