• Journal of Advanced Navigation Technology
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• v.10 no.2
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• pp.145-151
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• 2006

In this paper, we propose a novel navigation method combined Nearness Diagram, Limit-Cycle method and the Vector Field Method for avoidance of unexpected obstacles in the dynamic environment. The Limit-Cycle method is used to obstacle avoidance in front of the robot and the Vector Field Method is used to obstacle avoidance in the side of robot. And the Nearness Diagram Navigation is used to obstacle avoidance in the nearness area of the robot. The performance of the proposed method is demonstrate by simulations.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.348-353
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• 2020

This paper presents an adaptive method to avoid obstacles in various environmental settings, using a two-dimensional (2D) LiDAR sensor for mobile robots. While the conventional reaction based smooth nearness diagram (SND) algorithms use a fixed safety distance criterion, the proposed algorithm autonomously changes the safety criterion considering the obstacle density around a robot. The fixed safety criterion for the whole SND obstacle avoidance process can induce inefficient motion controls in terms of the travel distance and action smoothness. We applied a multinomial logistic regression algorithm, softmax regression, to classify 2D LiDAR point clouds into seven obstacle structure classes. The trained model was used to recognize a current obstacle density situation using newly obtained 2D LiDAR data. Through the classification, the robot adaptively modifies the safety distance criterion according to the change in its environment. We experimentally verified that the motion controls generated by the proposed adaptive algorithm were smoother and more efficient compared to those of the conventional SND algorithms.