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.

A Hybrid Posture Stabilization Method for Mobile Robots

Gürkan Küçükyıldız, Suat Karakaya

In this study, a point stabilization scheme which takes into account static obstacles around wheeled mobile robots is proposed. Novelty of the algorithm lies under the consideration of the static obstacles and corporation with the static path planning method exact Euclidian distance transform (EEDT). For a given start point, goal point and static obstacle configuration, the EEDT algorithm determines the shortest path. This path is in an open-polygonal form due to the robot’s grid-based workspace. Tangent values of each vertex of the open-polygon are given to conventional model prediction control (MPC) based posture stabilization scheme as sub-start and sub-goal points. These sub points are given to MPC in a shiftedhorizon strategy to determine the stabilized trajectories between the vertex coordinates. Overall stabilized static trajectory is determined by combining the sub-trajectories independently calculated by MPC based posture stabilization algorithm. The experimental results which are performed in a 3D virtual reality interface, confirms that the developed scheme satisfies the posture stabilization criterion successfully in presence of static obstacles.