A Bug-Based Local Path Planning Method for Static and Dynamic Environments

Gürkan Küçükyıldız, Suat Karakaya

In this study, a local path planning method was proposed for both static and dynamic environments. In obstacle-free cases, the mobile robot was forced to basic motion-togoal movement. In case where direct movement towards the global target is not possible, the algorithm searches for possible gaps which satisfy certain clearance criteria. The gaps were detected by taking the gradient of one dimensional distance vector acquired from the SICK LMS100 Light Detection and Ranging (LIDAR) sensor. The detected gaps were filtered by various methods which finally led to the optimal gap. Points on the line passing through the optimal gap were evaluated through a cost function and the point having the minimum cost was assumed to be the current local target. The points which were close to the two opposite corners of the gap less than a certain threshold were discarded to avoid collision. The threshold was determined based on the robot size and the kinematic model. Proportional and integral (PI) speed controller for left and right steered wheels was adapted to the proposed method. A graphical user interface (GUI) was developed to visualize the outputs of the method. On the GUI, offline LMS100 vectors and location data were visualized considering differential drive kinematic constraints for the mobile robot. The algorithm was developed at MATLAB environment.

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