AGV motion prediction based obstacle collision threat detection method

Abstract

The invention discloses an AGV motion prediction-based obstacle collision threat detection method. The method comprises the following steps: S1, obtaining a current position posture of an AGV; S2, obtaining a navigation speed control instruction according to the current position and posture of the AGV in combination with the navigation planning path; S3, receiving online temporary obstacle detection, and calculating an obstacle threat coefficient; S4, based on obstacle threat coefficients and via navigation speed control instructions, performing object avoidance determination, and if obstacleavoidance if necessary, performing obstacle avoidance speed control; the method is based on the contour of the AGV and AGV motion prediction. The obstacle threat of the AGV in the current motion stateis calculated according to the feedback data of the distance measuring sensor, so that the AGV can simply, reliably and timely discover the obstacle in the motion process; the detection speed and precision are only related to the characteristics of the AGV, and can be used as the input of subsequent AGV autonomous obstacle avoidance.

Description

technical field [0001] The invention relates to the field of AGVs, in particular to a detection method for obstacle collision threats based on AGV motion prediction. Background technique [0002] Generally, unmanned intelligent vehicles such as AGVs and intelligent inspection vehicles need to monitor temporary obstacles in real time during the walking process to avoid safety accidents caused by collisions. From the perspective of obstacle avoidance methods, on the one hand, the AGV must ensure a sufficient safety distance from obstacles to avoid false collisions caused by sensor errors or control accuracy errors. The passage is closed by a safe distance, causing a deadlock in AGV path planning. Therefore, the AGV obstacle avoidance algorithm in a dense and narrow environment has become an important component and core technology of the AGV navigation algorithm. [0003] The real-time feedback information of temporary obstacles is generally performed by laser ranging, sonar ...

AI Technical Summary

Problems solved by technology

The walking driving parts are generally servo motors and other driving devices. Errors caused by system delays, computer discrete precision, and encoder errors also cause certain errors between the driving parts and the actual walking of the AGV.

The above two errors are particularly serious during the high-speed walking of the AGV, and it is difficult to compensate. Moreover, the impact of this error is different in different environments, and it is difficult to perform pre-calibration

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