Abstract

In this paper, we propose an obstacle avoidance algorithm for a network-based autonomous mobile robot. The obstacle avoidance algorithm compensation based on the VFH(Vector Field Histogram) algorithm and delay-compensative methods is proposed for the network-based robot that is a unified system composed of distributed environmental sensors, mobile actuators, and the VFH controller. Firstly, the readings of the environmental sensors at a moment are compensated to the prospecting readings of the sensors considering a network delay measured and the kinematic model of a robot. The compensated readings of the sensors are used for building the polar histogram of the VFH algorithm. Secondly, a sensory fusion using the Kalman filter is proposed for the localization of the robot to compensate both the delay of readings of an odometry sensor and the delay of readings of environmental sensors. The performance enhancements of the proposed obstacle avoidance algorithm from the viewpoint of an efficient path generation and accurate goal positioning is also shown through some simulation experiments.

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