Improved VFH algorithm-based positioning and obstacle avoidance method and robot

Abstract

The invention provides an improved VFH algorithm-based positioning and obstacle avoidance method and robot. According to the improved VFH algorithm-based positioning and obstacle avoidance method and robot, on the basis of an improved vector field histogram method and a scan matching algorithm, environmental information is acquired by the adoption of a laser range-finder sensor, and the pose error brought by speedometer is amended by the adoption of the polar coordinate scan matching algorithm. After robot positioning is finished, environmental information is rasterized, an obstacle is expanded according to the relationship between the robot and the obstacle and considering the sensing uncertainty of a movable robot and the real size of the robot, an original polar coordinate histogram is built, the free walking area and the obstacle avoidance area are acquired, a binary polar coordinate histogram is acquired through the definition of two threshold values, a shielding polar coordinate histogram is built through estimating the movement trail of the movable robot, and finally, the cost function is introduced to determine the best movement direction of the robot so as to solve the problem of shielding route planning of the movable robot in a home environment.

Description

technical field [0001] This application relates to the field of autonomous navigation of intelligent robots, specifically to the field of ground creation and simultaneous positioning of robots, and in particular to a positioning and obstacle avoidance method based on an improved VFH algorithm and a robot. Background technique [0002] Intelligent robots, such as sweeping robots and robots, are more and more widely used in family life. To move flexibly, efficiently and intelligently, robots need to have autonomous navigation capabilities. Map Building, Location and Path Planning are the three key elements of autonomous navigation. The invention mainly relates to the field of map creation and simultaneous positioning. Among them, map creation and positioning are interdependent. Without an environmental map, the position of the robot cannot be accurately calibrated. If the initial position is uncertain, the created map lacks reference points. For this reason, the positioning ...

AI Technical Summary

Problems solved by technology

The advantage of the dead reckoning algorithm is that the pose of the robot is calculated by itself and does not require the perception information of the external environment. The disadvantage is that the drift error will accumulate over time. We know that any small error will increase infinitely after accumulation, so we need Consider error correction

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