Avoidance path planning method based on closest distance vector field histogram

Abstract

The invention provides an avoidance path planning method based on a closest distance vector field histogram. The avoidance path planning method comprises the following steps that S1 a current scanning range of a robot is evenly divided into n sectors, if the closest distance vector K between a barrier in the kth sector and the central point of the robot is NDVk, the result of |NDVk-1-NDVk | is obtained, the result is compared with the diameter of the robot, and the number of barriers in the local environment of the current position of the robot is obtained according to the comparison result; S2 a smallest barrier avoidance threshold ns is set, and if NDVk is larger than or equal to ns, the angle range of the sector k is a barrier avoidance region, and otherwise, the angle range of the sector k is a free walking region; S3 the searching range of an instantaneous target point is determined, the instantaneous target point is obtained from the searching range, after the robot moves to the instantaneous target point, a new instantaneous target point is determined, and the robot moves towards the new instantaneous target point until reaching the destination.

Description

technical field [0001] The invention relates to obstacle avoidance path planning of a robot, in particular to an obstacle avoidance path planning method based on the shortest distance vector field histogram. Background technique [0002] Robot obstacle avoidance path planning problem can be divided into two parts: global path planning with complete obstacle information a priori and local path planning with partially unknown or completely unknown obstacle information. The local path planning technology needs to make full use of the local environmental information collected by the robot's airborne sensors such as laser rangefinders and ultrasonic waves. Since the environment information of the robot cannot be fully obtained in advance, obstacle avoidance path planning in a completely unknown or partially unknown environment is the main capability of autonomous navigation. In this field, a large number of scholars at home and abroad have carried out corresponding research, amo...

AI Technical Summary

Problems solved by technology

However, this method has some disadvantages at the same time: first, it is prone to local poles and deadlocks; second, it cannot find paths between similar obstacles; third, it oscillates in front of obstacles; fourth, it swings in narrow passages; It is difficult to find a potential function suitable for concave obstacles

Fourth, when the VFH method selects the steering direction of the robot, it only considers the direction of the target, and does not consider the smoothness and stability of the robot's trajectory.

It is actually difficult for the robot to complete the predetermined trajectory calculated by the VFH algorithm

Fifth, the sensing information used by the VFH algorithm is also relative to the robot itself, which is easily affected by the robot's position uncertainty and sensing uncertainty

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