Preprint Article Version 1 This version is not peer-reviewed

Robot Path Planning Agent for Evaluating Collaborative Machine Behavior

Version 1 : Received: 21 May 2019 / Approved: 22 May 2019 / Online: 22 May 2019 (08:39:55 CEST)

How to cite: Ma, B.; Yang, H.; Wei, J.; Meng, Q. Robot Path Planning Agent for Evaluating Collaborative Machine Behavior. Preprints 2019, 2019050264 (doi: 10.20944/preprints201905.0264.v1). Ma, B.; Yang, H.; Wei, J.; Meng, Q. Robot Path Planning Agent for Evaluating Collaborative Machine Behavior. Preprints 2019, 2019050264 (doi: 10.20944/preprints201905.0264.v1).

Abstract

We first review the literature on machine behavior which may contain the interaction between machines, and then discuss the methodology and the related case involving collaboration between robots to instantiate the concept with AI empowerment. The navigation case aims to a security application with autonomous control and roadside agent embedded in a mobile edge computing structure. In the studied navigation based on the artificial potential field method, robots need to use position information to calculate the moving direction frequently. In the case of high motion speed as well as GPS positioning error, the path trajectory may show a sharp change of direction. In order to mitigate the trajectory oscillation, this paper proposes a path planning design where training process and motion direction prediction are integrated by using artificial neural network. The auxiliary navigation agent near multiple obstacles can first extract the past movement information of the robot and then determines whether there is a serious path jitter event. Computer simulation analysis shows that the combination of autonomous control and cooperative behavior can effectively reduce the path jitter so as to achieve a fast and safe path planning.

Subject Areas

machine behavior, mobile robots, navigation, path planning, artificial potential field, artificial neural network

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